Publication listings

This is a list of the publications, along with the NSF PAR status.

TODO: Needs an NSF PAR ID

For each of these, nsf-par-id: <number> should be added to the datafile. If an nsf-par-id really is not needed, set needs-nsf-par: false explicitly.

• _data/publications/2771676.yml: The derivation of Jacobian matrices for the propagation of track parameter uncertainties in the presence of magnetic fields and detector material, B. Yeo, H. Gray, A. Salzburger and S. Swatman, Nucl.Instrum.Meth.A 1068 169734 (2024) (25 Mar 2024).
• _data/publications/2765789.yml: Scalable ATLAS pMSSM computational workflows using containerised REANA reusable analysis platform, M. Donadoni, M. Feickert, L. Heinrich, Y. Liu, A. Mečionis, V. Moisieienkov, T. Šimko, G. Stark and M. García, EPJ Web Conf. 295 04035 (2024) (06 Mar 2024) [1 citation]. published in proceedings of CHEP 2023
• _data/publications/2743608.yml: Physics analysis for the HL-LHC: Concepts and pipelines in practice with the Analysis Grand Challenge, A. Held, E. Kauffman, O. Shadura and A. Wightman, EPJ Web Conf. 295 06016 (2024) (05 Jan 2024) [1 citation].
• _data/publications/2743013.yml: Machine Learning for Columnar High Energy Physics Analysis, E. Kauffman, A. Held and O. Shadura, EPJ Web Conf. 295 08011 (2024) (03 Jan 2024).
• _data/publications/2785725.yml: Data Management Package for the novel data delivery system, ServiceX, and Applications to various physics analysis workflows, K. Choi and P. Onyisi, EPJ Web Conf. 295 06008 (2024) (01 Jan 2024).
• _data/publications/2739807.yml: LHCb potential to discover long-lived new physics particles with lifetimes above 100 ps, V. Gorkavenko, B. Jashal, V. Kholoimov, Y. Kyselov, D. Mendoza, M. Ovchynnikov, A. Oyanguren, V. Svintozelskyi and J. Zhuo, Eur.Phys.J.C 84 608 (2024) (21 Dec 2023) [4 citations]. Includes work done by Fellows Valerii Kholoimov and Volodymyr Svintozelskyi
• _data/publications/2738584.yml: RenderCore – a new WebGPU-based rendering engine for ROOT-EVE, C. Bohak, D. Kovalskyi, S. Linev, A. Tadel, S. Strban, M. Tadel and A. Yagil, EPJ Web Conf. 295 03035 (2024) (18 Dec 2023).
• _data/publications/2738577.yml: Generalizing mkFit and its Application to HL-LHC, G. Cerati et. al., EPJ Web Conf. 295 03019 (2024) (18 Dec 2023).
• _data/publications/2738557.yml: Coffea-Casa: Building composable analysis facilities for the HL-LHC, S. Albin, G. Attebury, K. Bloom, B. Bockelman, C. Lundstedt, O. Shadura and J. Thiltges, EPJ Web Conf. 295 07009 (2024) (30 Nov 2023).
• _data/publications/2704887.yml: Bayesian Methodologies with pyhf, M. Feickert, L. Heinrich and M. Horstmann, EPJ Web Conf. 295 06004 (2024) (29 Sep 2023) [2 citations]. published in proceedings of CHEP 2023
• _data/publications/2703030.yml: Software Citation in HEP: Current State and Recommendations for the Future, M. Feickert, D. Katz, M. Neubauer, E. Sexton-Kennedy and G. Stewart, EPJ Web Conf. 295 08017 (2024) (25 Sep 2023). published in proceedings of CHEP 2023
• _data/publications/2701952.yml: Advances in developing deep neural networks for finding primary vertices in proton-proton collisions at the LHC, S. Akar, M. Elashri, R. Garg, E. Kauffman, M. Peters, H. Schreiner, M. Sokoloff, W. Tepe and L. Tompkins, EPJ Web Conf. 295 09003 (2024) (21 Sep 2023) [1 citation].
• _data/publications/2633642.yml: Evaluating query languages and systems for high-energy physics data, D. Graur, I. Müller, M. Proffitt, G. Fourny, G. Watts and G. Alonso, J.Phys.Conf.Ser. 2438 012034 (2023) (01 Jan 2023) [1 citation].
• _data/publications/2153585.yml: Snowmass 2021 Computational Frontier CompF4 Topical Group Report Storage and Processing Resource Access, W. Bhimji et. al., Comput.Softw.Big Sci. 7 5 (2023) (19 Sep 2022) [2 citations].
• _data/publications/snowmass2021-ML-event-generation.yml: Machine learning and LHC event generation, A. Butter et. al., SciPost Phys. 14 079 (2023) (14 Mar 2022) [77 citations]. Contribution to Snowmass 2021
• _data/publications/gpu-aas.yml: GPU-Accelerated Machine Learning Inference as a Service for Computing in Neutrino Experiments, M. Wang, T. Yang, M. Acosta Flechas, P. Harris, B. Hawks, B. Holzman, K. Knoepfel, J. Krupa, K. Pedro and N. Tran, Front.Big Data 3 604083 (2021) (09 Sep 2020) [20 citations]. this publication failed to acknowledge IRIS-HEP support
• _data/publications/1805478.yml: The Scikit HEP Project -- overview and prospects, E. Rodrigues et. al., EPJ Web Conf. 245 06028 (2020) (07 Jul 2020) [41 citations]. this publication failed to acknowledge IRIS-HEP support (or any other support)
• _data/publications/pivarski-chep2019-awkward1.yml: Awkward Arrays in Python, C++, and Numba, J. Pivarski, P. Elmer and D. Lange, EPJ Web Conf. 245 05023 (2020) (15 Jan 2020) [17 citations].
• _data/publications/pivarski-chep2018-columnar.yml: Columnar data processing for HEP analysis, J. Pivarsk, J. Nandi, D. Lange and P. Elmer, EPJ Web Conf. 214 06026 (2019) (17 Sep 2019) [4 citations].
• _data/publications/1683311.yml: Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model, Advances in Neural Information Processing Systems 33 (NeurIPS) (20 Jul 2018) [7 citations]. published, and acknowledges IRIS-HEP, but no DOI from NIPS proceedings website?

Has an NSF PAR ID

For each of these, nsf-par-id has been added.

• _data/publications/2633515.yml: Declarative interfaces for HEP data analysis: FuncADL and ADL/CutLang, C. Huh, M. Proffitt, H. Prosper, S. Sekmen, B. Sen, G. Unel and G. Watts, J.Phys.Conf.Ser. 2438 012075 (2023) (01 Jan 2023) [NSF PAR].
• _data/publications/2513684.yml: Deep Learning for the Matrix Element Method, M. Neubauer, M. Feickert, M. Katare and A. Roy, PoS ICHEP2022 246 (2022) (21 Nov 2022) [1 citation] [NSF PAR].
• _data/publications/2157930.yml: Segment Linking: A Highly Parallelizable Track Reconstruction Algorithm for HL-LHC, P. Chang et. al., J.Phys.Conf.Ser. 2375 012005 (2022) (27 Sep 2022) [1 citation] [NSF PAR].
• _data/publications/roy-fastjet-acat2021.yml: An array-oriented Python interface for FastJet, A. Roy, J. Pivarski and C. Freer, J.Phys.Conf.Ser. 2438 012011 (2023) (08 Feb 2022) [NSF PAR].
• _data/publications/1993309.yml: A non-linear Kalman filter for track parameters estimation in high energy physics, X. Ai, H. Gray, A. Salzburger and N. Styles, Nucl.Instrum.Meth.A 1049 168041 (2023) (17 Dec 2021) [2 citations] [NSF PAR].
• _data/publications/1983941.yml: Graph Neural Networks for Charged Particle Tracking on FPGAs, A. Elabd et. al., Front.Big Data 5 828666 (2022) (03 Dec 2021) [25 citations] [NSF PAR].
• _data/publications/1951634.yml: Applications and Techniques for Fast Machine Learning in Science, A. Deiana et. al., Front.Big Data 5 787421 (2022) (25 Oct 2021) [34 citations] [NSF PAR].
• _data/publications/1919763.yml: Publishing statistical models: Getting the most out of particle physics experiments, K. Cranmer et. al., SciPost Phys. 12 037 (2022) (10 Sep 2021) [40 citations] [NSF PAR].
• _data/publications/1911884.yml: Evolutionary Algorithms for Tracking Algorithm Parameter Optimization, P. Chatain, R. Garg and L. Tompkins, EPJ Web Conf. 251 03071 (2021) (23 Aug 2021) [2 citations] [NSF PAR].
• _data/publications/1911802.yml: Building and steering binned template fits with cabinetry, K. Cranmer and A. Held, EPJ Web Conf. 251 03067 (2021) (23 Aug 2021) [10 citations] [NSF PAR].
• _data/publications/1870330.yml: A Common Tracking Software Project, X. Ai et. al., Comput.Softw.Big Sci. 6 8 (2022) (25 Jun 2021) [69 citations] [NSF PAR].
• _data/publications/1864766.yml: Reframing Jet Physics with New Computational Methods, The 25th International Conference on Computing in High-Energy and Nuclear Physics, vCHEP 2021. (21 May 2021) [9 citations] [NSF PAR].
• _data/publications/1862170.yml: A GPU-Based Kalman Filter for Track Fitting, X. Ai, G. Mania, H. Gray, M. Kuhn and N. Styles, Comput.Softw.Big Sci. 5 20 (2021) (04 May 2021) [6 citations] [NSF PAR].
• _data/publications/1854743.yml: Charged Particle Tracking via Edge-Classifying Interaction Networks, G. DeZoort, S. Thais, J. Duarte, V. Razavimaleki, M. Atkinson, I. Ojalvo, M. Neubauer and P. Elmer, Comput.Softw.Big Sci. 5 26 (2021) (30 Mar 2021) [38 citations] [NSF PAR].
• _data/publications/1852909.yml: hep_tables: Heterogeneous Array Programming for HEP, Watts, Gordon, EPJ Web Conf. 251 03061 (2021) (21 Mar 2021) [NSF PAR].
• _data/publications/1851403.yml: Performance of a geometric deep learning pipeline for HL-LHC particle tracking, X. Ju et. al., Eur.Phys.J.C 81 876 (2021) (11 Mar 2021) [46 citations] [NSF PAR].
• _data/publications/1851623.yml: TRACER (TRACe route ExploRer): A tool to explore OSG/WLCG network route topologies, E. Tretyakov, A. Artamonov, M. Grigorieva, A. Klimentov, S. McKee and I. Vukotic, Int.J.Mod.Phys.A 36 2130005 (2021) (10 Mar 2021) [NSF PAR].
• _data/publications/1850625.yml: Progress in developing a hybrid deep learning algorithm for identifying and locating primary vertices, S. Akar, G. Atluri, T. Boettcher, M. Peters, H. Schreiner, M. Sokoloff, M. Stahl, W. Tepe, C. Weisser and M. Williams, EPJ Web Conf. 251 04012 (2021) (08 Mar 2021) [4 citations] [NSF PAR].
• _data/publications/1849745.yml: Distributed statistical inference with pyhf enabled through funcX, M. Feickert, L. Heinrich, G. Stark and B. Galewsky, EPJ Web Conf. 251 02070 (2021) (03 Mar 2021) [2 citations] [NSF PAR].
• _data/publications/1849748.yml: FuncADL: Functional Analysis Description Language, M. Proffitt and G. Watts, EPJ Web Conf. 251 03068 (2021) (02 Mar 2021) [8 citations] [NSF PAR].
• _data/publications/1849648.yml: Coffea-casa: an analysis facility prototype, M. Adamec, G. Attebury, K. Bloom, B. Bockelman, C. Lundstedt, O. Shadura and J. Thiltges, EPJ Web Conf. 251 02061 (2021) (02 Mar 2021) [13 citations] [NSF PAR].
• _data/publications/1849307.yml: Software Training in HEP, S. Malik et. al., Comput.Softw.Big Sci. 5 22 (2021) (28 Feb 2021) [5 citations] [NSF PAR].
• _data/publications/1849306.yml: An intelligent Data Delivery Service for and beyond the ATLAS experiment, W. Guan, T. Maeno, B. Bockelman, T. Wenaus, F. Lin, S. Padolski, R. Zhang and A. Alekseev, EPJ Web Conf. 251 02007 (2021) (28 Feb 2021) [8 citations] [NSF PAR].
• _data/publications/pivarski-chep2021-awkwardforth.yml: AwkwardForth: accelerating Uproot with an internal DSL, J. Pivarski, I. Osborne, P. Das, D. Lange and P. Elmer, EPJ Web Conf. 251 03002 (2021) (24 Feb 2021) [1 citation] [NSF PAR].
• _data/publications/1845084.yml: pyhf: pure-Python implementation of HistFactory statistical models, L. Heinrich, M. Feickert, G. Stark and K. Cranmer, J.Open Source Softw. 6 2823 (2021) (04 Feb 2021) [146 citations] [NSF PAR].
• _data/publications/1831598.yml: Recent developments in histogram libraries, H. Dembinski, J. Pivarski and H. Schreiner, EPJ Web Conf. 245 05014 (2020) (20 Nov 2020) [3 citations] [NSF PAR].
• _data/publications/1832223.yml: Constraining effective field theories with machine learning, J. Brehmer, K. Cranmer, I. Espejo, A. Held, F. Kling, G. Louppe and J. Pavez, EPJ Web Conf. 245 06026 (2020) (16 Nov 2020) [3 citations] [NSF PAR].
• _data/publications/1811378.yml: Sampling using SU(N) gauge equivariant flows, D. Boyda, G. Kanwar, S. Racanière, D. Rezende, M. Albergo, K. Cranmer, D. Hackett and P. Shanahan, Phys.Rev.D 103 074504 (2021) (12 Aug 2020) [108 citations] [NSF PAR].
• _data/publications/1810547.yml: Secondary vertex finding in jets with neural networks, J. Shlomi, S. Ganguly, E. Gross, K. Cranmer, Y. Lipman, H. Serviansky, H. Maron and N. Segol, Eur.Phys.J.C 81 540 (2021) (06 Aug 2020) [28 citations] [NSF PAR].
• _data/publications/1808088.yml: GPU coprocessors as a service for deep learning inference in high energy physics, J. Krupa et. al., Mach.Learn.Sci.Tech. 2 035005 (2021) (20 Jul 2020) [26 citations] [NSF PAR].
• _data/publications/pivarski-acat2019-awkward.yml: Nested data structures in array frameworks, J. Pivarski, D. Lange and P. Elmer, J.Phys.Conf.Ser. 1525 012053 (2020) (07 Jul 2020) [1 citation] [NSF PAR].
• _data/publications/1804620.yml: WLCG Networks: Update on Monitoring and Analytics, M. Babik, S. McKee, P. Andrade, B. Bockelman, R. Gardner, E. Fajardo Hernandez, E. Martelli, I. Vukotic, D. Weitzel and M. Zvada, EPJ Web Conf. 245 07053 (2020) (01 Jul 2020) [1 citation] [NSF PAR].
• _data/publications/1804608.yml: Network Capabilities for the HL-LHC Era, M. Babik and S. McKee, EPJ Web Conf. 245 07051 (2020) (01 Jul 2020) [NSF PAR].
• _data/publications/1798734.yml: Speeding up particle track reconstruction using a parallel Kalman filter algorithm, S. Lantz et. al., JINST 15 P09030 (2020) (29 May 2020) [13 citations] [NSF PAR].
• _data/publications/1796248.yml: The Scalable Systems Laboratory: a Platform for Software Innovation for HEP, R. Gardner, L. Bryant, M. Neubauer, F. Wuerthwein, J. Stephen and A. Chien, EPJ Web Conf. 245 05019 (2020) (13 May 2020) [NSF PAR].
• _data/publications/1785309.yml: Equivariant flow-based sampling for lattice gauge theory, G. Kanwar, M. Albergo, D. Boyda, K. Cranmer, D. Hackett, S. Racanière, D. Rezende and P. Shanahan, Phys.Rev.Lett. 125 121601 (2020) (13 Mar 2020) [160 citations] [NSF PAR].
• _data/publications/1781096.yml: Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm, G. Cerati et. al., EPJ Web Conf. 245 02013 (2020) (15 Feb 2020) [3 citations] [NSF PAR].
• _data/publications/1771853.yml: Allen: A high level trigger on GPUs for LHCb, R. Aaij et. al., Comput.Softw.Big Sci. 4 7 (2020) (19 Dec 2019) [83 citations] [NSF PAR].
• _data/publications/1752736.yml: Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning, The Astrophysical Journal, Volume 886, Number 1; DOI:10.3847/1538-4357/ab4c41 (19 Nov 2019) [77 citations] [NSF PAR]. published in Astrophysical Journal, see citation.
• _data/publications/dahlgren-pdsw19.yml: Towards Physical Design Management in Storage Systems, Kathryn Dahlgren, Jeff LeFevre, Ashay Shirwadkar, Ken Iizawa, Aldrin Montana, Peter Alvaro, Carlos Maltzahn, 4th International Parallel Data Systems Workshop (PDSW 2019, co-located with SC’19), Denver, CO, November 18, 2019. (18 Nov 2019) [NSF PAR].
• _data/publications/1763198.yml: The frontier of simulation-based inference, Proceedings of the National Academy of Sciences DOI:10.1073/pnas.1912789117 (04 Nov 2019) [232 citations] [NSF PAR].
• _data/publications/1746275.yml: MadMiner: Machine learning-based inference for particle physics, J. Brehmer, F. Kling, I. Espejo and K. Cranmer, Comput.Softw.Big Sci. 4 3 (2020) (24 Jul 2019) [105 citations] [NSF PAR].
• _data/publications/1742890.yml: Etalumis: bringing probabilistic programming to scientific simulators at scale, Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19), November 17--22, 2019 DOI:10.1145/3295500.3356180 (07 Jul 2019) [12 citations] [NSF PAR].
• _data/publications/1740667.yml: A hybrid deep learning approach to vertexing, R. Fang, H. Schreiner, M. Sokoloff, C. Weisser and M. Williams, J.Phys.Conf.Ser. 1525 012079 (2020) (19 Jun 2019) [6 citations] [NSF PAR].
• _data/publications/1738733.yml: Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures with the CMS Detector, G. Cerati et. al., J.Phys.Conf.Ser. 1525 012078 (2020) (05 Jun 2019) [3 citations] [NSF PAR].
• _data/publications/1738305.yml: Effective LHC measurements with matrix elements and machine learning, J. Brehmer, K. Cranmer, I. Espejo, F. Kling, G. Louppe and J. Pavez, J.Phys.Conf.Ser. 1525 012022 (2020) (04 Jun 2019) [17 citations] [NSF PAR].
• _data/publications/1730403.yml: FPGA-accelerated machine learning inference as a service for particle physics computing, J. Duarte et. al., Comput.Softw.Big Sci. 3 13 (2019) (18 Apr 2019) [29 citations] [NSF PAR].
• _data/publications/1726790.yml: Machine learning and the physical sciences, G. Carleo, I. Cirac, K. Cranmer, L. Daudet, M. Schuld, N. Tishby, L. Vogt-Maranto and L. Zdeborová, Rev.Mod.Phys. 91 045002 (2019) (25 Mar 2019) [745 citations] [NSF PAR].
• _data/publications/1722059.yml: The Machine Learning landscape of top taggers, G. Kasieczka et. al., SciPost Phys. 7 014 (2019) (26 Feb 2019) [218 citations] [NSF PAR].

No explicit request for ID

These do not have NSF PAR IDs, and probably do not need one; either because they are arXiv only, have an explicit false for needs-nsf-par, or were manually entered. Many of the arXiv publications are preprints for papers submitted to journals or to the proceedings of various conferences, and will eventually need an NSF PAR ID once published.

• _data/publications/2828774.yml: Exploring code portability solutions for HEP with a particle tracking test code, H. Ather et. al., arXiv 2409.09228 (13 Sep 2024).
• _data/publications/2811026.yml: Line Segment Tracking: Improving the Phase 2 CMS High Level Trigger Tracking with a Novel, Hardware-Agnostic Pattern Recognition Algorithm, E. Vourliotis et. al., arXiv 2407.18231 (25 Jul 2024).
• _data/publications/feickert-scipy-2024.yml: How the Scientific Python ecosystem helps answer fundamental questions of the Universe, Matthew Feickert, Nikolai Hartmann, Lukas Heinrich, Alexander Held, Vangelis Kourlitis, Nils Krumnack, Giordon Stark, Matthias Vigl, Gordon Watts, SciPy 2024 (10 Jul 2024).
• _data/publications/osborne-acat2024-bridging-worlds-language-interoperability.yml: Bridging Worlds: Achieving Language Interoperability between Julia and Python in Scientific Computing, I. Osborne, J. Pivarski and J. Ling, arXiv 2404.18170 (Submitted to ACAT 2024) (28 Apr 2024).
• _data/publications/2773393.yml: Analysis Facilities White Paper, D. Ciangottini et. al., arXiv 2404.02100 (02 Apr 2024). Work done by the HSF Analysis Facilities forum
• _data/publications/feickert-cern-ep-newsletter-2024-03.yml: Extending ATLAS Physics Reach with Analysis Reuse Technology, Matthew Feickert, CERN EP Newsletter (10 Mar 2024). CERN EP Newsletter, March 2024
• _data/publications/klieret_ctd.yml: High Pileup Particle Tracking with Object Condensation, Kilian Lieret, Gage DeZoort, Devdoot Chatterjee, Jian Park, et.al. High Pileup Particle Tracking with Object Condensation. Submitted to 8th International Connecting The Dots Workshop (Toulouse 2023) (06 Dec 2023).
• _data/publications/CHEP2023-TrainToSustain.yml: Train To Sustain, Sudhir Malik, Kilian Lieret, Peter Elmer, Michel Hernandez Villanueva, and Stefan Roiser (15 Nov 2023).
• _data/publications/TrainingAndOnboarding.yml: Training and Onboarding initiatives in High Energy Physics experiments, S. Hageboeck, A. Reinsvold Hall, N. Skidmore, G. A. Stewart, G. Benelli, B. Carlson, C. David, J. Davies, W. Deconinck, D. DeMuth Jr., P. Elmer, R. B. Garg, K. Lieret, V. Lukashenko, S. Malik, A. Morris, H. Schellman, J. Veatch, M. Hernandez Villanueva (23 Oct 2023).
• _data/publications/osborne-chep2023-awkward-jit.yml: Awkward Just-In-Time (JIT) Compilation: A Developer's Experience, Ianna Osborne, Jim Pivarski, Ioana Ifrim, Angus Hollands and Henry Schreiner, arXiv:2310.01461 [cs.PL] (Submitted to CHEP 2023) (03 Oct 2023).
• _data/publications/klieret_chep.yml: An Object Condensation Pipeline for Charged Particle Tracking, Kilian Lieret and Gage DeZoort. An Object Condensation Pipeline for Charged Particle Tracking. Submitted to 8th International Connecting The Dots Workshop (Toulouse 2023) (28 Sep 2023).
• _data/publications/Outreach-IRIS-HEP-CHEP2023.yml: Software Training Outreach In HEP , Sudhir Malik, Danelix Cordero, Peter Elmer, Adam LaMee, and Ken Cecire (24 Sep 2023).
• _data/publications/Deng-xcache-SNTA-2023.yml: Analyzing Transatlantic Network Traffic over Scientific Data Caches, Ziyue Deng, Alex Sim, Kesheng Wu, Chin Guok, Inder Monga, Fabio Andrijauskas, Frank Wuerthwein, and Derek Weitzel. Analyzing Transatlantic Network Traffic over Scientific Data Caches. in ACM 6th International Workshop on System and Network Telemetry and Analytics (SNTA'23) (20 Jun 2023).
• _data/publications/singh-ipdps23.yml: Fast And Automatic Floating Point Error Analysis With CHEF-FP, Garima Singh, Baidyanath Kundu, Harshitha Menon, Alexander Penev, David J. Lange and Vassil Vassilev, arXiv:2304.06441 [math.NA] (Submitted to IEEE International Parallel and Distributed Processing Symposium 2023) (13 Apr 2023).
• _data/publications/oshadura-alheld-agc-acat2022.yml: First performance measurements with the Analysis Grand Challenge, Oksana Shadura, Alexander Held, arXiv:2304.05214 [hep-ex] (Submitted to ACAT 2022) (12 Apr 2023).
• _data/publications/2650794.yml: Speeding up the CMS track reconstruction with a parallelized and vectorized Kalman-filter-based algorithm during the LHC Run 3, S. Berkman et. al., arXiv 2304.05853 (12 Apr 2023) [2 citations].
• _data/publications/2650787.yml: Scaling MadMiner with a deployment on REANA, I. Espejo, S. Perez, K. Hurtado, L. Heinrich and K. Cranmer, arXiv 2304.05814 (12 Apr 2023).
• _data/publications/2650465.yml: Equivariant Graph Neural Networks for Charged Particle Tracking, D. Murnane, S. Thais and A. Thete, arXiv 2304.05293 (11 Apr 2023) [8 citations].
• _data/publications/2649275.yml: Comparing and improving hybrid deep learning algorithms for identifying and locating primary vertices, S. Akar, M. Peters, H. Schreiner, M. Sokoloff and W. Tepe, arXiv 2304.02423 (05 Apr 2023) [2 citations].
• _data/publications/singh-acat23.yml: Automatic Differentiation of Binned Likelihoods With Roofit and Clad, Garima Singh, Jonas Rembser, Lorenzo Moneta, David Lange and Vassil Vassilev, arXiv:2304.02650 [cs.MS] (Submitted to ACAT 2023) (04 Apr 2023).
• _data/publications/2647709.yml: Progress towards an improved particle flow algorithm at CMS with machine learning, F. Mokhtar, J. Pata, J. Duarte, E. Wulff, M. Pierini and J. Vlimant, arXiv 2303.17657 (30 Mar 2023) [7 citations].
• _data/publications/roy-acat2022-awkwardforth-uproot.yml: Using a DSL to read ROOT TTrees faster in Uproot, A. Roy and J. Pivarski, arXiv 2303.02202 (Submitted to ACAT 2022) (03 Mar 2023).
• _data/publications/goyal-acat2022-awkward-cpp.yml: The Awkward World of Python and C++, M. Goyal, I. Osborne and J. Pivarski, arXiv 2303.02205 (Submitted to ACAT 2022) (03 Mar 2023) [1 citation].
• _data/publications/ddavila-ICNC23.yml: Effectiveness and predictability of in-network storage cache for Scientific Workflows, Caitlin Sim, Kesheng Wu, Alex Sim, Inder Monga, Chin Guok, Frank Würthwein, Diego Davila, Harvey Newman, and Justas Balcas. 2023 (22 Feb 2023).
• _data/publications/osborne-acat2022-awkward-rdataframe.yml: Awkward to RDataFrame and back, I. Osborne and J. Pivarski, arXiv 2302.09860 (Submitted to ACAT 2022) (20 Feb 2023) [3 citations].
• _data/publications/lst-ctd23.yml: Improving tracking algorithms with machine learning: a case for line-segment tracking at the High Luminosity LHC, Jonathan Guiang, Slava Krutelyov, Manos Vourliotis, Yanxi Gu, Avi Yagil, Balaji Venkat Sathia Narayanan, Matevz Tadel, Philip Chang, Mayra Silva, Gavin Niendorf, Peter Wittich, Tres Reid, Peter Elmer (for the CMS Collaboration), arXiv:2403.13166 (2023). (Submitted to CTD 2023) (Submitted to CTD 2023) (02 Feb 2023).
• _data/publications/2628983.yml: IRIS-HEP Strategic Plan for the Next Phase of Software Upgrades for HL-LHC Physics, B. Bockelman et. al., arXiv 2302.01317 (02 Feb 2023).
• _data/publications/2598491.yml: pyhf: a pure-Python statistical fitting library with tensors and automatic differentiation, M. Feickert, L. Heinrich and G. Stark, arXiv 2211.15838 (28 Nov 2022) [5 citations].
• _data/publications/2598292.yml: The IRIS-HEP Analysis Grand Challenge, A. Held and O. Shadura, Unknown (26 Nov 2022) [4 citations].
• _data/publications/2182396.yml: LHC EFT WG Report: Experimental Measurements and Observables, N. Castro, K. Cranmer, A. Gritsan, J. Howarth, G. Magni, K. Mimasu, J. Rojo, J. Roskes, E. Vryonidou and T. You, arXiv 2211.08353 (15 Nov 2022) [12 citations].
• _data/publications/rucio-sense-xloop22.yml: Managed Network Services for Exascale Data Movement Across Large Global Scientific Collaborations, F. Wurthwein, J. Guiang, A. Arora, D. Davila, J. Graham, D. Mishin, T. Hutton, I. Sfiligoi, H. Newman, J. Balcas, T. Lehman, X. Yang, and C. Guok, Managed network services for exascale data movement across large global scientific collaborations, in 2022 4th Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP), (Los Alamitos, CA, USA), pp. 16–19, IEEE Computer Society, November, 2022. (14 Nov 2022).
• _data/publications/2175469.yml: Exploration of different parameter optimization algorithms within the context of ACTS software framework, R. Garg, E. Hofgard, L. Tompkins and H. Gray, arXiv 2211.00764 (01 Nov 2022) [1 citation].
• _data/publications/2164496.yml: The Future of High Energy Physics Software and Computing, V. Elvira et. al., arXiv 2210.05822 (11 Oct 2022) [5 citations].
• _data/publications/2154231.yml: Making Digital Objects FAIR in High Energy Physics: An Implementation for Universal FeynRules Output (UFO) Models, M. Neubauer, A. Roy and Z. Wang, arXiv 2209.09752 (20 Sep 2022) [2 citations].
• _data/publications/liu-hpec22.yml: Processing Particle Data Flows with SmartNICs, Jianshen Liu, Carlos Maltzahn, Matthew L. Curry, Craig Ulmer. Towards an Arrow-native Storage System. 2022 IEEE High Performance Extreme Computing Conference (HPEC), Virtual, September 19-23, 2022. Outstanding Student Paper (19 Sep 2022).
• _data/publications/2153139.yml: Reinterpretation and Long-Term Preservation of Data and Code, S. Bailey, K. Cranmer, M. Feickert, R. Fine, S. Kraml and C. Lange, arXiv 2209.08054 (16 Sep 2022) [3 citations].
• _data/publications/zakaria-sc22.yml: Mapping Out the HPC Dependency Chaos, Farid Zakaria, Thomas R. W. Scogland, Todd Gamblin, and Carlos Maltzahn. Mapping out the hpc dependency chaos. In SC22, Dallas, TX, November 13-18 2022. (27 Aug 2022).
• _data/publications/aew2-report.yml: HSF IRIS-HEP Second Analysis Ecosystem Workshop Report, 10.5281/zenodo.7003962 (17 Aug 2022).
• _data/publications/schreiner-SciPy22.yml: Awkward Packaging: building Scikit-HEP, Henry Schreiner, Jim Pivarski, Eduardo Rodrigues, SciPy 2022 (14 Jul 2022).
• _data/publications/rucio-sense-pearc22.yml: Integrating End-to-End Exascale SDN into the LHC Data Distribution Cyberinfrastructure, Jonathan Guiang, Aashay Arora, Diego Davila, John Graham, Dima Mishin, Igor Sfiligoi, Frank Wuerthwein, Tom Lehman, Xi Yang, Chin Guok, Harvey Newman, Justas Balcas, and Thomas Hutton. 2022. Integrating End-to-End Exascale SDN into the LHC Data Distribution Cyberinfrastructure. In Practice and Experience in Advanced Research Computing (PEARC '22). Association for Computing Machinery, New York, NY, USA, Article 53, 1–4. https://doi.org/10.1145/3491418.3535134 (08 Jul 2022).
• _data/publications/malik-precs22.yml: Expanding the Scope of Artifact Evaluation at HPC Conferences: Experience of SC21, Tanu Malik, Anjo Vahldiek-Oberwagner, Ivo Jimenez, Carlos Maltzahn. Expanding the Scope of Artifact Evaluation at HPC Conferences: Experience of SC21. 5th International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS), Virtual, June 30, 2022. (30 Jun 2022).
• _data/publications/chakraborty-ccgrid22.yml: Skyhook: Towards an Arrow-Native Storage System, Chakraborty, J., Jimenez, I., Rodriguez, S.A., Uta, A., LeFevre, J. and Maltzahn, C., 2021. Towards an Arrow-native Storage System. The 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid'22), Taormina (Messina), Italy, May 16-19, 2022. (16 May 2022).
• _data/publications/ddavila-snta22-2.yml: Access Trends of In-network Cache for Scientific Data, Ruize Han, Alex Sim, Kesheng Wu, Inder Monga, Chin Guok, Frank Würthwein, Diego Davila, Justas Balcas, Harvey Newman. 2022 (11 May 2022).
• _data/publications/ddavila-snta22-1.yml: Studying Scientific Data Lifecycle in On-demand Distributed Storage Caches, Julian Bellavita, Alex Sim, Kesheng Wu, Inder Monga, Chin Guok, Frank Würthwein, Diego Davila. 2022 (11 May 2022).
• _data/publications/2060087.yml: Physics Community Needs, Tools, and Resources for Machine Learning, P. Harris et. al., arXiv 2203.16255 (30 Mar 2022) [10 citations].
• _data/publications/2057973.yml: Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges, S. Thais, P. Calafiura, G. Chachamis, G. DeZoort, J. Duarte, S. Ganguly, M. Kagan, D. Murnane, M. Neubauer and K. Terao, arXiv 2203.12852 (23 Mar 2022) [32 citations].
• _data/publications/snowmass2021-preservation-reinterpretation.yml: Data and Analysis Preservation, Recasting, and Reinterpretation, S. Bailey et. al., arXiv 2203.10057 (18 Mar 2022) [13 citations]. Contribution to Snowmass 2021
• _data/publications/Snowmass2021-ParticlePhysicsOutreachtoK-12SchoolsandOpportunitiesinUndergraduateEducation.yml: Particle Physics Outreach to K-12 Schools and Opportunities in Undergraduate Education, Marge G. Bardeen, Olivia M. Bitter, Marla Glover, Sijbrand J. de Jong, Tiffany R. Lewis, Michael Fetsko, Adam LaMee, Christian Rosenzweig, Deborah Roudebush, Andrew D. Santos, Shane Wood, Kenneth Cecire, Randal Ruchti, Guillermo Fidalgo, Sudhir Malik (15 Mar 2022).
• _data/publications/Snowmass2021-FacilitatingNon-HEPCareerTransition_.yml: Facilitating Non-HEP Career Transition , Sudhir Malik, Aneliya Karadzhinova-Ferrer, Julie Hogan, Rachel Bray, Rami Kamalieddin, Kevin Flood, Amr El-Zant, Guillermo Fidalgo, David Bruhwiler, Matt Bellis (15 Mar 2022).
• _data/publications/Snowmass2021-BroadeningEducationCareeerOpenScienceInHEP.yml: Broadening the scope of Education, Career and Open Science in HEP, Sudhir Malik, David DeMuth, Sijbrand de Jong, Randal Ruchti, Savannah Thais, Guillermo Fidalgo, Ken Heller, Mathew Muether, Minerba Betancourt, Meenakshi Narain, Tiffany R. Lewis, Kyle Cranmer, Gordon Watts (15 Mar 2022).
• _data/publications/Snowmass-EnhancingHEP-ResearchInPredominantlyUndergraduateInstitutionsAndCommunityColleges.yml: Enhancing HEP research in predominantly undergraduate institutions and community colleges, Matt Bellis, Bhubanjyoti Bhattacharya, David DeMuth, Julie Hogan, Kathrine Laureto, Sudhir Malik, Ben Pearson (15 Mar 2022).
• _data/publications/software-training-ACAT2021.yml: Software Training in High Energy Physics, Michel H. Villanueva, Sudhir Malik, Meirin Oan Evans, ACAT2021, J. Phys.: Conf. Ser. 2438 012063 (07 Mar 2022).
• _data/publications/pivarski-lhcc-pythonecosystem.yml: HL-LHC Computing Review Stage 2: Common Software Projects: Data Science Tools for Analysis, J. Pivarski, E. Rodrigues, K. Pedro, O. Shadura, B. Krikler and G. Stewart, arXiv 2202.02194 (04 Feb 2022) [4 citations].
• _data/publications/1997105.yml: The Quantum Trellis: A classical algorithm for sampling the parton shower with interference effects, S. Macaluso and K. Cranmer, arXiv 2112.12795 (23 Dec 2021) [2 citations].
• _data/publications/thais_graphseg_neurips2021.yml: Graph Segmentation in Scientific Datasets, R. Sahay and S. Thais, Graph Segmentation in Scientific Datasets, Submitted to the Machine Learning and the Physical Sciences workshop at NeurIPS 2021 (13 Dec 2021).
• _data/publications/1984823.yml: The Service Analysis and Network Diagnosis DataPipeline, D. Weitzel, S. McKee, B. Bockelman, J. Thiltges, M. Babik and I. Vukotic, arXiv 2112.03074 (06 Dec 2021).
• _data/publications/rodriguez-bigdata21.yml: Zero-Cost, Arrow-Enabled Data Interface for Apache Spark, Rodriguez, S.A., Chakraborty, J., Chu, A., Jimenez, I., LeFevre, J., Maltzahn, C. and Uta, A., 2021. Zero-Cost, Arrow-Enabled Data Interface for Apache Spark. 2021 IEEE International Conference on Biog Data (IEEE BigData 2021), Virtual, December 15-18, 2021. (27 Nov 2021).
• _data/publications/chakraborty-arxiv-2.yml: Zero-Cost, Arrow-Enabled Data Interface for Apache Spark, Rodriguez, S.A., Chakraborty, J., Chu, A., Jimenez, I., LeFevre, J., Maltzahn, C. and Uta, A., 2021. Zero-Cost, Arrow-Enabled Data Interface for Apache Spark. arXiv preprint arXiv:2106.13020. (27 Nov 2021).
• _data/publications/1976818.yml: Explaining machine-learned particle-flow reconstruction, F. Mokhtar, R. Kansal, D. Diaz, J. Duarte, J. Pata, M. Pierini and J. Vlimant, arXiv 2111.12840 (24 Nov 2021) [10 citations].
• _data/publications/chakraborty-medium-skyhook-release.yml: SkyhookDM is now a part of Apache Arrow!, (25 Oct 2021).
• _data/publications/k_choi_chep2021.yml: Towards Real-World Applications of ServiceX, an Analysis Data Transformation System, K. Choi, A. Eckart, B. Galewsky, R. Gardner, M. Neubauer, P. Onyisi, M. Proffitt, I. Vukotic and G. Watts (23 Aug 2021).
• _data/publications/1873328.yml: Learning from the Pandemic: the Future of Meetings in HEP and Beyond, M. Neubauer et. al., arXiv 2106.15783 (29 Jun 2021).
• _data/publications/1869687.yml: Particle Cloud Generation with Message Passing Generative Adversarial Networks, R. Kansal, J. Duarte, H. Su, B. Orzari, T. Tomei, M. Pierini, M. Touranakou, J. Vlimant and D. Gunopulos, arXiv 2106.11535 (22 Jun 2021) [47 citations].
• _data/publications/ddavila-snta21.yml: Analyzing scientific data sharing patterns for in-network data caching, Elizabeth Copps, Huiyi Zhang, Alex Sim, Kesheng Wu, Inder Monga, Chin Guok, Frank Würthwein, Diego Davila, and Edgar Fajardo. 2021 (21 Jun 2021).
• _data/publications/chakraborty-arxiv-1.yml: Towards an Arrow-native Storage System, Chakraborty, J., Jimenez, I., Rodriguez, S.A., Uta, A., LeFevre, J. and Maltzahn, C., 2021. Towards an Arrow-native Storage System. arXiv preprint arXiv:2105.09894. (21 May 2021).
• _data/publications/1860769.yml: Evaluating Query Languages and Systems for High-Energy Physics Data [Extended Version], D. Graur, I. Müller, M. Proffitt, G. Fourny, G. Watts and G. Alonso, arXiv 2104.12615 (26 Apr 2021) [5 citations].
• _data/publications/1858493.yml: Exact and Approximate Hierarchical Clustering Using A*, The Conference on Uncertainty in Artificial Intelligence (UAI) 2021. (14 Apr 2021).
• _data/publications/efajardo-chep21-http-tpc.yml: Systematic benchmarking of HTTPS third party copy on 100Gbps links using XRootD, Fajardo, Edgar, Aashay Arora, Diego Davila, Richard Gao, Frank Würthwein, and Brian Bockelman, arXiv:2103.12116 (2021). (Submitted to CHEP 2019) (22 Mar 2021).
• _data/publications/instanceseg_gnn_2020.yml: Instance Segmentation GNNs for One-Shot Conformal Tracking at the LHC, S. Thais and G. DeZoort, arXiv 2103.06509 (21 Mar 2021) [6 citations].
• _data/publications/1834621.yml: Accelerated Charged Particle Tracking with Graph Neural Networks on FPGAs, A. Heintz et. al., arXiv 2012.01563 (30 Nov 2020) [22 citations].
• _data/publications/servicex-CHEP.yml: ServiceX A Distributed, Caching, Columnar Data Delivery Service, ServiceX A Distributed, Caching, Columnar Data Delivery Service B. Galewsky, R. Gardner, L. Gray, M. Neubauer, J. Pivarski, M. Proffitt, I. Vukotic, G. Watts, M. Weinberg EPJ Web Conf. 245 04043 (2020) DOI: 10.1051/epjconf/202024504043 (16 Nov 2020).
• _data/publications/1830592.yml: Hierarchical clustering in particle physics through reinforcement learning, Machine Learning and the Physical Sciences, Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS), December 11, 2020 (16 Nov 2020) [4 citations].
• _data/publications/chakraborty-sc20.yml: Enabling Seamless Execution of Computational and Data Science Workflows on HPC and Cloud with the Popper Container-Native Automation Engine, Chakraborty J, Maltzahn C, and Jimenez I. 2020 2nd International Workshop on Containers and New Orchestration Paradigms for Isolated Environments in HPC (CANOPIE-HPC, co-located with SC'20) (12 Nov 2020).
• _data/publications/1824092.yml: Semi-parametric gamma-ray modeling with Gaussian processes and variational inference, S. Mishra-Sharma and K. Cranmer, arXiv 2010.10450 (20 Oct 2020) [10 citations].
• _data/publications/fpga-aas.yml: FPGAs-as-a-Service Toolkit (FaaST), D. Rankin et. al., arXiv 2010.08556 (16 Oct 2020) [17 citations].
• _data/publications/1823735.yml: FPGAs-as-a-Service Toolkit (FaaST), D. Rankin et. al., arXiv 2010.08556 (16 Oct 2020) [17 citations].
• _data/publications/1822448.yml: Simulation-based inference methods for particle physics, J. Brehmer and K. Cranmer, arXiv 2010.06439 (13 Oct 2020) [15 citations].
• _data/publications/chakraborty-summer2021-fellowship.yml: Reproducible, Scalable Benchmarks for SkyhookDM using Popper, Chakraborty J. IRIS-HEP Summer 2020 Fellowship Report (12 Oct 2020).
• _data/publications/1822229.yml: Software Sustainability & High Energy Physics, D. Katz et. al., arXiv 2010.05102 (10 Oct 2020).
• _data/publications/snowmass2021-analysis-ecosystem-loi.yml: Snowmass 2021 Letter of Interest: Analysis Ecosystem at the HL-LHC, G. Watts Snowmass 2021 Letter of Interest (10 Sep 2020).
• _data/publications/snowmass2021-training.yml: Snowmass2021 Letter of Interest : Coherent Vision for Enabling Software Training in HEP, Daniel S. Katz, Clemens Lange, Kilian Lieret, Sudhir Malik, Samuel Meehan, Kevin Nelson, Robin Newhouse, Meirin Oan Evans, Adam Parker, Mason Proffitt, Eduardo Rodrigues, Amber Roepe, Giordon Stark, Graeme Stewart, Sadhana Verma, Leonora Vesterbacka, and Claire David, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-sustainability.yml: Snowmass 2021 Letter of Interest: Software Sustainability and HEP, Daniel S. Katz, Sudhir Malik, Mark S. Neubauer, and Graeme A. Stewart, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-reproducibility.yml: Snowmass 2021 Letter of Interest: Long Term Reproducibility and Sustainability of Scientific Software, Matthew Feickert, Giordon Stark, Steven Gardiner, and Yu-Dai Tsai, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-emerging-techniques-jets.yml: Snowmass 2021 Letter of Interest: Emerging Computational Techniques for Jet Physics, Sebastian Macaluso, Kyle Cranmer, Matthew Drnevich, Johann Brehmer (New York University); Duccio Pappadopulo (N.A.); Atılım Gunes Baydin (Oxford); Matthew Schwartz (Harvard), Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-differentiable-programming.yml: Snowmass 2021 Letter of Interest: Differentiable Programming in High-Energy Physics, Atilim Gunes Baydin, Kyle Cranmer, Matthew Feickert, Lindsey Gray, Lukas Heinrich, Alexander Held, Andrew Melo, Mark Neubauer, Jannicke Pearkes, Nathan Simpson, Nick Smith, Giordon Stark, Savannah Thais, Vassil Vassilev, and Gordon Watts, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-boost.yml: Snowmass 2021 Letter of Interest: Jets and Jet Substructure at Future Colliders, The BOOST Community, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-MLedu.yml: Snowmass 2021 Letter of Interest: Particle Physics and Machine Learning in Education, Mark S. Neubauer, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-MLMELA.yml: Snowmass 2021 Letter of Interest: Matrix Element Method in the Machine Learning Era, P. Chang, M. Feickert, and Mark S. Neubauer, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-GNNs.yml: Snowmass 2021 Letter of Interest: Graph Data Structures and Graph Neural Networks for High Energy Physics, X. Ju, M. Neubauer, L. Gray, A. Aurisano, T. R. F. P. Tomei, J.-R. Vlimant, J. Hewes, K. Terao, S. Thais, D. Murnane, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/snowmass2021-FastML.yml: Snowmass 2021 Letter of Interest: Fast Machine Learning, M.-A. Flechas, M. Atkinson, G.-Di Guglielmo, J. Duarte, F. Fahim, P. Harris, C. Herwig, B. Holzman, R. Kastner, M. Liu, C.-S. Moon, M. Neubauer, K. Pedro, A.-Q. Parra, D. Rankin, R. Rivera, N. Tran, M. Wang, T. Yang, J. Agar9, and E.-A. Huerta, Snowmass 2021 Letters of Interest (31 Aug 2020).
• _data/publications/schreiner-SciPy20.yml: Boost-histogram: High-Performance Histograms as Objects, Henry Schreiner, Hans Dembinski, Shuo Liu, Jim Pivarski, SciPy 2020 (07 Jul 2020).
• _data/publications/pivarski-scipy2020-awkward.yml: Awkward Array: JSON-like data, NumPy-like idioms, Jim Pivarski, Ianna Osborne, Pratyush Das, Anish Biswas, Peter Elmer, SciPy 2020 (07 Jul 2020).
• _data/publications/1804843.yml: Tracking with A Common Tracking Software, Ai, Xiaocong, arXiv 2007.01239 (02 Jul 2020) [3 citations].
• _data/publications/1804768.yml: An updated hybrid deep learning algorithm for identifying and locating primary vertices, S. Akar, T. J. Boettcher, S. Carl, H. F. Schreiner, M. D. Sokoloff, M. Stahl, C. Weisser, M. Williams, arXiv:2007.01023 [physics.ins-det] (Submitted to CTD2020) (02 Jul 2020).
• _data/publications/povm-medrxiv.yml: Inexpensive multi-patient respiratory monitoring system for helmet ventilation during COVID-19 pandemic, Philippe Bourrianne, Stanley Chidzik, Daniel Cohen, Peter Elmer, Thomas Hallowell, Todd J. Kilbaugh, David Lange, Andrew M. Leifer, Daniel R. Marlow, Peter D. Meyers, Edna Normand, Janine Nunes, Myungchul Oh, Lyman Page, Talmo Periera, Jim Pivarski, Henry Schreiner, Howard A. Stone, David W. Tank, Stephan Thiberge and Christopher Tully, medRxiv https://doi.org/10.1101/2020.06.29.20141283 (30 Jun 2020). medRxiv preprint
• _data/publications/1802414.yml: Discovering Symbolic Models from Deep Learning with Inductive Biases, M. Cranmer, A. Sanchez-Gonzalez, P. Battaglia, R. Xu, K. Cranmer, D. Spergel and S. Ho, arXiv 2006.11287 (19 Jun 2020) [57 citations].
• _data/publications/liu-hotedge20.yml: Scale-out Edge Storage Systems with Embedded Storage Nodes to Get Better Availability and Cost-Efficiency At the Same Time, Jianshen Liu, Matthew Leon Curry, Carlos Maltzahn, and Philip Kufeldt, 3rd USENIX Workshop on Hot Topics in Edge Computing (HotEdge ’20), Santa Clara, CA, June 25-26 2020 (26 May 2020).
• _data/publications/lefevre-login20.yml: SkyhookDM: Data Processing in Ceph with Programmable Storage, Jeff LeFevre and Carlos Maltzahn, USENIX ;login: Magazine (12 May 2020).
• _data/publications/1789128.yml: Flows for simultaneous manifold learning and density estimation, Advances in Neural Information Processing Systems 34 (NeurIPS2020) (30 Mar 2020) [27 citations].
• _data/publications/wguan-chep19.yml: Towards an Intelligent Data Delivery Service, Wen Guan, Tadashi Maeno, Gancho Dimitrov, Brian Paul Bockelman, Torre Wenaus, Vakhtang Tsulaia, Nicolo Magini, CHEP2019 (14 Mar 2020).
• _data/publications/beomki_yeo_ACAT_2021.yml: Detray: a compile time polymorphic tracking geometry description (submitted), Andreas Salzburger, Joana Niermann, Beomki Yeo, Attila Krasznahorkay, ACAT 2021 (27 Feb 2020).
• _data/publications/uta-nsdi19.yml: Is big data performance reproducible in modern cloud networks?, Alexandru Uta, Alexandru Custura, Dmitry Duplyakin, Ivo Jimenez, Jan Rellermeyer, Carlos Maltzahn, Robert Ricci, and Alexandru Iosup, 17th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’20), Santa Clara, CA, February 25-27 2020 (26 Feb 2020).
• _data/publications/1782435.yml: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering, The 24th International Conference on Artificial Intelligence and Statistics, PMLR 130:2467-2475, 2021. (26 Feb 2020) [3 citations].
• _data/publications/lefevre-vault20.yml: Scaling databases and file APIs with programmable Ceph object storage, Jeff LeFevre and Carlos Maltzahn, 2020 Linux Storage and Filesystems Conference (Vault'20, co-located with FAST'20 and NSDI'20), Santa Clara, CA, February 24-25 2020 (24 Feb 2020). This is a presentation at Usenix conference
• _data/publications/1781879.yml: Set2Graph: Learning Graphs From Sets, Advances in Neural Information Processing Systems 34 (NeurIPS2020) (20 Feb 2020) [12 citations].
• _data/publications/1779199.yml: Normalizing Flows on Tori and Spheres, Thirty-seventh International Conference on Machine Learning (06 Feb 2020) [18 citations]. Accepted at Thirty-seventh International Conference on Machine Learning
• _data/publications/chakraborty-ecp20.yml: Popper 2.0: A Container-native Workflow Execution Engine For Testing Complex Applications and Validating Scientific Claims, Jayjeet Chakraborty, Ivo Jimenez, Carlos Maltzahn, Arshul Mansoori, and Quincy Wofford, Poster at 2020 Exaxcale Computing Project Annual Meeting, Houston, TX, February 3-7, 2020, 2020 (03 Feb 2020).
• _data/publications/efajardo-chep19-xcache-cdn.yml: Creating a content delivery network for general science on the internet backbone using XCaches, Edgar Fajardo and Marian Zvada and Derek Weitzel and Mats Rynge and John Hicks and Mat Selmeci and Brian Lin and Pascal Paschos and Brian Bockelman and Igor Sfiligoi and Andrew Hanushevsky and Frank Würthwein, arXiv:2007.01408 [cs.DC] (Submitted to CHEP 2019) (08 Nov 2019).
• _data/publications/chu-chep19.yml: SkyhookDM: Mapping Scientific Datasets to Programmable Storage, Aaron Chu and Jeff LeFevre and Carlos Maltzahn and Aldrin Montana and Peter Alvaro and Dana Robinson and Quincey Koziol, arXiv:2007.01789 [cs.DS] (Submitted to CHEP 2019) (08 Nov 2019).
• _data/publications/bbockelm-chep19-tokens.yml: WLCG Authorisation from X.509 to Tokens, Brian Bockelman and Andrea Ceccanti and Ian Collier and Linda Cornwall and Thomas Dack and Jaroslav Guenther and Mario Lassnig and Maarten Litmaath and Paul Millar and Mischa Sallé and Hannah Short and Jeny Teheran and Romain Wartel, arXiv:2007.03602 [cs.CR] (Submitted to CHEP 2019) (08 Nov 2019).
• _data/publications/bbockelm-chep19-http-tpc.yml: Third-party transfers in WLCG using HTTP, Brian Bockelman and Andrea Ceccanti and Fabrizio Furano and Paul Millar and Dmitry Litvintsev and Alessandra Forti, arXiv:2007.03490 [cs.DC] (Submitted to CHEP 2019) (08 Nov 2019).
• _data/publications/1760401.yml: Extending RECAST for Truth-Level Reinterpretations, A. Schuy, L. Heinrich, K. Cranmer and S. Hsu, arXiv 1910.10289 (Submitted to APS DPF 2019) (22 Oct 2019) [1 citation].
• _data/publications/1758014.yml: Acts: A common tracking software, Ai, Xiaocong, arXiv 1910.03128 (07 Oct 2019) [11 citations].
• _data/publications/1758925.yml: Hamiltonian Graph Networks with ODE Integrators, A. Sanchez-Gonzalez, V. Bapst, K. Cranmer and P. Battaglia, arXiv 1909.12790 (Submitted to Machine Learning For the Physical Sciences NeurIPS2019 Workshop) (27 Sep 2019) [11 citations]. presented at Machine Learning For the Physical Sciences NeurIPS2019 Workshop - missing IRIS-HEP acknowledgement
• _data/publications/atlas-recast.yml: RECAST framework reinterpretation of an ATLAS Dark Matter Search constraining a model of a dark Higgs boson decaying to two b-quarks, ATL-PHYS-PUB-2019-032 (12 Aug 2019). ATLAS PUB NOTE
• _data/publications/atlas-pyhf.yml: Reproducing searches for new physics with the ATLAS experiment through publication of full statistical likelihoods, ATL-PHYS-PUB-2019-029 (05 Aug 2019). ATLAS PUB NOTE
• _data/publications/1741870.yml: Speeding up Particle Track Reconstruction in the CMS Detector using a Vectorized and Parallelized Kalman Filter Algorithm, G. Cerati et. al., arXiv 1906.11744 (Submitted to CTD/WIT 2019) (27 Jun 2019) [4 citations].
• _data/publications/david-precs19.yml: Reproducible Computer Network Experiments: A Case Study Using Popper, Andrea David, Mariette Souppe, Ivo Jimenez, Katia Obraczka, Sam Mansfield, Kerry Veenstra, Carlos Maltzahn, 2nd International Workshop on Practical Reproducible Evaluation of Computer Systems (P-RECS, co-located with HPDC’19), Phoenix, AZ, June 24, 2019. (24 Jun 2019). DOI?
• _data/publications/liu-hpc-iodc19.yml: MBWU: Benefit Quantification for Data Access Function Offloading, Jianshen Liu, Philip Kufeldt, Carlos Maltzahn, HPC I/O in the Data Center Workshop (HPC-IODC 2019, co-located with ISC-HPC 2019), Frankfurt, Germany, June 20, 2019. (20 Jun 2019). No Ackwowledgements? DOI?
• _data/publications/lefevre-vault19.yml: Skyhook: Programmable storage for databases, Jeff LeFevre, Noah Watkins, Michael Sevilla, and Carlos Maltzahn, 2020 Linux Storage and Filesystems Conference (Vault'19, co-located with FAST'19), Santa Clara, CA, February 25-26 2019 (25 Feb 2019). This is a presentation at Usenix conference
• _data/publications/hep_analysis_ecosystem_ws_report_2017.yml: HEP Analysis Ecosystem Workshop Report, Elmer, Peter, Mato, Pere, Sexton-Kennedy, Elizabeth, & Wenaus, Torre. (2017). HEP Analysis Ecosystem Workshop Report https://indico.cern.ch/event/613842/ (04 Sep 2017).

Prior or related work

These do not need to have NSF PAR IDs (at least for IRIS-HEP purposes) as they are prior or related work.

• _data/publications/2613273.yml: FAIR AI models in high energy physics, J. Duarte et. al., Mach.Learn.Sci.Tech. 4 045062 (2023) (09 Dec 2022) [5 citations].
• _data/publications/2514167.yml: Interpretability of an Interaction Network for identifying H \rightarrow b\bar{b} jets, A. Roy and M. Neubauer, arXiv 2211.12770 (23 Nov 2022) [2 citations].
• _data/publications/2163245.yml: A detailed study of interpretability of deep neural network based top taggers, A. Khot, M. Neubauer and A. Roy, Mach.Learn.Sci.Tech. 4 035003 (2023) (09 Oct 2022) [10 citations].
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