John Salvatier
Publications by Year
Research Areas
Computational Physics and Python Applications, COVID-19 epidemiological studies, Gaussian Processes and Bayesian Inference, Bayesian Modeling and Causal Inference, COVID-19 Pandemic Impacts
Most-Cited Works
- → Probabilistic programming in Python using PyMC3(2016)2,482 cited
- → Inferring the effectiveness of government interventions against COVID-19(2020)1,110 cited
- → The effectiveness of eight nonpharmaceutical interventions against COVID-19 in 41 countries(2020)89 cited
- PyMC3: Python probabilistic programming framework(2016)
- → Thousands of AI Authors on the Future of AI(2025)21 cited
- → pymc-devs/pymc3: PyMC3 3.11.2 (14 March 2021)(2021)6 cited
- → epidemics/COVIDNPIs: Inferring the effectiveness of government interventions against COVID-19(2020)
- → pymc-devs/pymc3: PyMC3 3.11.4 (20 August 2021)(2021)
- → Peer Review #2 of "Probabilistic programming in Python using PyMC3 (v0.1)"(2016)