3 papers
cs.LG2020
Uncertainty in Neural Processes
Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy +1
We explore the effects of architecture and training objective choice on amortized posterior predictive inference in probabilistic conditional generative models. We aim this work to…
cs.LG2020
Coping With Simulators That Don't Always Return
Andrew Warrington, Saeid Naderiparizi, Frank Wood
Deterministic models are approximations of reality that are easy to interpret and often easier to build than stochastic alternatives. Unfortunately, as nature is capricious, observ…
cs.LG2019
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Atılım Güneş Baydin, Lei Shao, Wahid Bhimji +14
Probabilistic programming languages (PPLs) are receiving widespread attention for performing Bayesian inference in complex generative models. However, applications to science remai…