Publications:
by date.
Publications by the IRIS-HEP team
- Hamiltonian Graph Networks with ODE Integrators, Alvaro Sanchez-Gonzalez, Victor Bapst, Kyle Cranmer, Peter Battaglia [arXiv:1909.12790] (27 Sep 2019).
- Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning, J. Brehmer, S. Mishra-Sharma, J. Hermans, G. Louppe and K. Cranmer, arXiv 1909.02005 (04 Sep 2019).
- Benchmarking simplified template cross sections in $WH$ production, J. Brehmer, S. Dawson, S. Homiller, F. Kling and T. Plehn, arXiv 1908.06980 (19 Aug 2019).
- MadMiner: Machine learning-based inference for particle physics, J. Brehmer, F. Kling, I. Espejo and K. Cranmer, arXiv 1907.10621 (24 Jul 2019).
- Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale, A. Baydin, L. Shao, W. Bhimji, L. Heinrich, L. Meadows et. al., arXiv 1907.03382 (07 Jul 2019).
- A hybrid deep learning approach to vertexing, R. Fang, H. Schreiner, M. Sokoloff, C. Weisser and M. Williams, arXiv 1906.08306 (Submitted to ACAT 2019) (19 Jun 2019).
- Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures with the CMS Detector, G. Cerati, P. Elmer, B. Gravelle, M. Kortelainen, V. Krutelyov et. al., arXiv 1906.02253 (05 Jun 2019).
- Effective LHC measurements with matrix elements and machine learning, J. Brehmer, K. Cranmer, I. Espejo, F. Kling, G. Louppe et. al., arXiv 1906.01578 (04 Jun 2019).
- FPGA-Accelerated Machine Learning Inference as a Service for Particle Physics Computing, J. Duarte, P. Harris, S. Hauck, B. Holzman, S. Hsu et. al., arXiv 1904.08986 (18 Apr 2019).
- Machine learning and the physical sciences, G. Carleo, I. Cirac, K. Cranmer, L. Daudet, M. Schuld et. al., arXiv 1903.10563 (25 Mar 2019).
- The Machine Learning Landscape of Top Taggers, G. Kasieczka, T. Plehn, A. Butter, K. Cranmer, D. Debnath et. al., SciPost Phys. 7 014 (2019) (26 Feb 2019).
- Open is not enough, X. Chen, S. Dallmeier-Tiessen, R. Dasler, S. Feger, P. Fokianos et. al., Nature Phys. 15 (2019) (15 Nov 2018).
- Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model, A. Baydin, L. Heinrich, W. Bhimji, L. Shao, S. Naderiparizi et. al., arXiv 1807.07706 (20 Jul 2018).
- Strategic Plan for a Scientific Software Innovation Institute (S2I2) for High Energy Physics, P. Elmer, M. Neubauer and M. Sokoloff, arXiv 1712.06592 (18 Dec 2017).
- A Roadmap for HEP Software and Computing R&D for the 2020s, J. Albrecht, A. Alves, G. Amadio, G. Andronico, N. Anh-Ky et. al., Comput.Softw.Big Sci. 3 7 (2019) (18 Dec 2017).
- Adversarial Variational Optimization of Non-Differentiable Simulators, G. Louppe, J. Hermans and K. Cranmer, arXiv 1707.07113 (22 Jul 2017).
- QCD-Aware Recursive Neural Networks for Jet Physics, G. Louppe, K. Cho, C. Becot and K. Cranmer, JHEP 01 057 (2019) (02 Feb 2017).