PPX is a cross-platform Probabilistic Programming eXecution protocol and API based on flatbuffers. It is intended as an open interoperability protocol between models and inference engines implemented in different probabilistic programming languages. PPX is related to pyprob, a PyTorch-based library for probabilistic programming and inference compilation. See Atılım Güneş Baydin’s keynote talk at ACAT2019.
This work led to the following publicatoins:
“Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model”, arXiv:1807.07706 ) published in NeurIPS2019.
“Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale”, A. Baydin, L. Shao, W. Bhimji, L. Heinrich, L. Meadows et. al., published in SC19 arXiv:1907.03382 https://dl.acm.org/doi/10.1145/3295500.3356180 (07 Jul 2019)
PPX protocol and
pyprob tool have since been applied to epidemiological studies such as “Hijacking Malaria Simulators with Probabilistic Programming”, arXiv:1905.12432 and are now being applied to COVID19 (see “Planning as inference in epidemiological dynamics models” by Warrington, A., Naderiparizi, S., Weilbach, C., Masrani, V., Harvey, W., Scibior, A., Beronov, B., & Nasseri, A. (2020) arXiv:2003.13221 ).
- Kyle Cranmer
- Atılım Güneş Baydin
- Tuan Anh Le
- Lukas Heinrich
- Wahid Bhimji
- Kyle Cranmer
- Frank Wood
- 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) [2 citations] [NSF PAR].
- Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model, Advances in Neural Information Processing Systems 33 (NeurIPS) (20 Jul 2018) [3 citations].