Discontinuous Hamiltonian Monte Carlo for Probabilistic Programs. - Bradley Gram-Hansen; Yuan Zhou 013; Tobias Kohn; Hongseok Yang; Frank D. Wood (CoRR, 2018)

On Exploration, Exploitation and Learning in Adaptive Importance Sampling. - Xiaoyu Lu; Tom Rainforth; Yuan Zhou 013; Jan-Willem van de Meent; Yee Whye Teh (CoRR, 2018)

LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models. - Yuan Zhou 013; Bradley J. Gram-Hansen; Tobias Kohn; Tom Rainforth; Hongseok Yang; Frank Wood (AISTATS, 2019)

Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support. - Yuan Zhou 013; Hongseok Yang; Yee Whye Teh; Tom Rainforth (ICML, 2020)

Stochastically Differentiable Probabilistic Programs. - David Tolpin; Yuan Zhou 013; Hongseok Yang (CoRR, 2020)

Probabilistic Programs with Stochastic Conditioning. - David Tolpin; Yuan Zhou 013; Hongseok Yang (CoRR, 2020)

Bayesian Policy Search for Stochastic Domains. - David Tolpin; Yuan Zhou 013; Hongseok Yang (CoRR, 2020)

Automating inference for non-standard models. - Yuan Zhou 013 (2020)

Probabilistic Programs with Stochastic Conditioning. - David Tolpin; Yuan Zhou 013; Tom Rainforth; Hongseok Yang (ICML, 2021)