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A New Approach to Probabilistic Programming Inference

3 July 2015

Frank Wood

Jan-Willem van de Meent

Vikash K. Mansinghka

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Papers citing "A New Approach to Probabilistic Programming Inference"

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Title
Unfolding AlphaFold's Bayesian Roots in Probability Kinematics T. Hamelryck K. Mardia AI4CE 11 0 0 26 May 2025
Language-Based Security for Low-Level MPC Christian Skalka Joseph P. Near 118 1 0 23 Jul 2024
Automated Statistical Model Discovery with Language Models Michael Y. Li Emily B. Fox Noah D. Goodman 86 19 0 27 Feb 2024
Efficient Incremental Belief Updates Using Weighted Virtual Observations David Tolpin 45 0 0 10 Feb 2024
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support Tim Reichelt C. Ong Tom Rainforth 63 2 0 01 Nov 2023
Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support Tim Reichelt C.-H. Luke Ong Tom Rainforth 59 0 0 23 Oct 2023
Heterogeneous Multi-Task Gaussian Cox Processes Feng Zhou Quyu Kong Zhijie Deng Fengxiang He Peng Cui Jun Zhu 97 2 0 29 Aug 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 78 0 0 10 Jun 2023
Declarative Probabilistic Logic Programming in Discrete-Continuous Domains Pedro Zuidberg Dos Martires Luc de Raedt Angelika Kimmig 94 4 0 21 Feb 2023
Automatically Marginalized MCMC in Probabilistic Programming Jinlin Lai Javier Burroni Hui Guan Daniel Sheldon 87 3 0 01 Feb 2023
Nonparametric Involutive Markov Chain Monte Carlo Carol Mak Fabian Zaiser C. Ong 65 1 0 02 Nov 2022
Nonlinear System Identification: Learning while respecting physical models using a sequential Monte Carlo method A. Wigren Johan Wågberg Fredrik Lindsten A. Wills Thomas B. Schon 50 11 0 26 Oct 2022
Learning and Compositionality: a Unification Attempt via Connectionist Probabilistic Programming Ximing Qiao Hai Helen Li 20 0 0 26 Aug 2022
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference Wonyeol Lee Xavier Rival Hongseok Yang 96 10 0 22 Aug 2022
Generative Models: An Interdisciplinary Perspective Kris Sankaran Susan P. Holmes AI4CE 31 8 0 11 Aug 2022
Designing Perceptual Puzzles by Differentiating Probabilistic Programs Kartik Chandra Tzu-Mao Li J. Tenenbaum Jonathan Ragan-Kelley AAML 39 21 0 26 Apr 2022
Querying Labelled Data with Scenario Programs for Sim-to-Real Validation Edward Kim Jay Shenoy Sebastian Junges Daniel J. Fremont Alberto L. Sangiovanni-Vincentelli Sanjit A. Seshia 78 3 0 01 Dec 2021
GaussED: A Probabilistic Programming Language for Sequential Experimental Design Matthew A. Fisher Onur Teymur Chris J. Oates 92 1 0 15 Oct 2021
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan-Willem van de Meent BDL 80 21 0 21 Jun 2021
Nonparametric Hamiltonian Monte Carlo Carol Mak Fabian Zaiser C.-H. Luke Ong 60 6 0 18 Jun 2021
Expectation Programming: Adapting Probabilistic Programming Systems to Estimate Expectations Efficiently Tim Reichelt Adam Goliñski C.-H. Luke Ong Tom Rainforth TPM 60 0 0 09 Jun 2021
Meta-Learning an Inference Algorithm for Probabilistic Programs Gwonsoo Che Hongseok Yang TPM 35 1 0 01 Mar 2021
Learning Proposals for Probabilistic Programs with Inference Combinators Sam Stites Heiko Zimmermann Hao Wu Eli Sennesh Jan-Willem van de Meent NAI 84 16 0 01 Mar 2021
Accelerating Metropolis-Hastings with Lightweight Inference Compilation Feynman T. Liang Nimar S. Arora N. Tehrani Y. Li Michael Tingley E. Meijer 50 0 0 23 Oct 2020
Conditional independence by typing Maria I. Gorinova Andrew D. Gordon Charles Sutton Matthijs Vákár 75 15 0 22 Oct 2020
Scenic: A Language for Scenario Specification and Data Generation Daniel J. Fremont Edward J. Kim T. Dreossi Shromona Ghosh Xiangyu Yue Alberto L. Sangiovanni-Vincentelli Sanjit A. Seshia 82 99 0 13 Oct 2020
Simulation-based inference methods for particle physics Johann Brehmer Kyle Cranmer AI4CE 126 22 0 13 Oct 2020
Neuro-symbolic Neurodegenerative Disease Modeling as Probabilistic Programmed Deep Kernels Alexander Lavin BDL MedIm 79 9 0 16 Sep 2020
An invitation to sequential Monte Carlo samplers Chenguang Dai J. Heng Pierre E. Jacob N. Whiteley 132 68 0 23 Jul 2020
PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming Alexander K. Lew Monica Agrawal David Sontag Vikash K. Mansinghka 134 28 0 23 Jul 2020
Scaling Bayesian inference of mixed multinomial logit models to very large datasets Filipe Rodrigues BDL 100 3 0 11 Apr 2020
Planning as Inference in Epidemiological Models Frank Wood Andrew Warrington Saeid Naderiparizi Christian D. Weilbach Vaden Masrani ... Adam Scibior Boyan Beronov John Grefenstette Duncan Campbell Alireza Nasseri 59 6 0 30 Mar 2020
Stochastically Differentiable Probabilistic Programs David Tolpin Yuanshuo Zhou Hongseok Yang BDL 37 0 0 02 Mar 2020
DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models Mohamed Tarek Kai Xu Martin Trapp Hong Ge Zoubin Ghahramani 43 7 0 07 Feb 2020
Stochastic Probabilistic Programs David Tolpin Tomer Dobkin 39 0 0 08 Jan 2020
Blang: Bayesian declarative modelling of general data structures and inference via algorithms based on distribution continua Alexandre Bouchard-Côté Kevin Chern Davor Cubranic Sahand Hosseini Justin Hume Matteo Lepur Zihui Ouyang G. Sgarbi 31 6 0 22 Dec 2019
Differentiable Algorithm for Marginalising Changepoints Hyoungjin Lim Gwonsoo Che Wonyeol Lee Hongseok Yang 28 1 0 22 Nov 2019
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 266 857 0 04 Nov 2019
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support Yuanshuo Zhou Hongseok Yang Yee Whye Teh Tom Rainforth TPM 70 20 0 29 Oct 2019
Attention for Inference Compilation William Harvey Andreas Munk A. G. Baydin Alexander Bergholm Frank Wood 57 9 0 25 Oct 2019
Probabilistic Surrogate Networks for Simulators with Unbounded Randomness Andreas Munk Berend Zwartsenberg Adam Scibior A. G. Baydin Andrew Stewart G. Fernlund A. Poursartip Frank Wood TPM 66 4 0 25 Oct 2019
Amortized Rejection Sampling in Universal Probabilistic Programming Saeid Naderiparizi Adam Scibior Andreas Munk Mehrdad Ghadiri A. G. Baydin ... R. Zinkov Philip Torr Tom Rainforth Yee Whye Teh Frank Wood 69 7 0 20 Oct 2019
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming Yura N. Perov L. Graham Kostis Gourgoulias Jonathan G. Richens Ciarán M. Gilligan-Lee Adam Baker Saurabh Johri LRM 60 17 0 17 Oct 2019
Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs Víctor Gallego D. Insua BDL 44 1 0 26 Aug 2019
Population Predictive Checks Rajesh Ranganath David M. Blei Rajesh Ranganath 64 13 0 02 Aug 2019
Towards Verified Stochastic Variational Inference for Probabilistic Programs Wonyeol Lee Hangyeol Yu Xavier Rival Hongseok Yang 70 26 0 20 Jul 2019
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling Feras A. Saad Marco F. Cusumano-Towner Ulrich Schaechtle Martin Rinard Vikash K. Mansinghka 58 62 0 14 Jul 2019
Deployable probabilistic programming David Tolpin TPM 104 7 0 20 Jun 2019
Declarative Learning-Based Programming as an Interface to AI Systems Parisa Kordjamshidi Dan Roth Kristian Kersting 74 4 0 18 Jun 2019
The Random Conditional Distribution for Higher-Order Probabilistic Inference Zenna Tavares Xin Zhang Edgar Minaysan Javier Burroni Rajesh Ranganath Armando Solar-Lezama 45 9 0 25 Mar 2019