LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models

6 March 2019

Papers citing "LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models"

7 / 7 papers shown

Title
Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming Raven Beutner Luke Ong Fabian Zaiser 16 11 0 06 Apr 2022
Conditional independence by typing Maria I. Gorinova Andrew D. Gordon Charles Sutton Matthijs Vákár 24 14 0 22 Oct 2020
On Correctness of Automatic Differentiation for Non-Differentiable Functions Wonyeol Lee Hangyeol Yu Xavier Rival Hongseok Yang 15 40 0 12 Jun 2020
Stochastically Differentiable Probabilistic Programs David Tolpin Yuanshuo Zhou Hongseok Yang BDL 11 0 0 02 Mar 2020
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support Yuanshuo Zhou Hongseok Yang Yee Whye Teh Tom Rainforth TPM 29 19 0 29 Oct 2019
Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables Guangyao Zhou 19 19 0 11 Sep 2019
MCMC using Hamiltonian dynamics Radford M. Neal 185 3,266 0 09 Jun 2012