Inference Compilation and Universal Probabilistic Programming

31 October 2016

Papers citing "Inference Compilation and Universal Probabilistic Programming"

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Title
Compositional simulation-based inference for time series Manuel Gloeckler S. Toyota Kenji Fukumizu Jakob H Macke 45 1 0 05 Nov 2024
Combining Induction and Transduction for Abstract Reasoning Wen-Ding Li Keya Hu Carter Larsen Yuqing Wu Simon Alford ... Dat Nguyen Wei-Long Zheng Zenna Tavares Yewen Pu Kevin Ellis AI4CE 35 7 0 04 Nov 2024
Amortized Bayesian Multilevel Models Daniel Habermann Marvin Schmitt Lars Kühmichel Andreas Bulling Stefan T. Radev Paul-Christian Burkner 67 3 0 23 Aug 2024
All-in-one simulation-based inference Manuel Gloeckler Michael Deistler Christian Weilbach Frank D. Wood Jakob H. Macke 34 26 0 15 Apr 2024
Efficient Incremental Belief Updates Using Weighted Virtual Observations David Tolpin 14 0 0 10 Feb 2024
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support Tim Reichelt C. Ong Tom Rainforth 22 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 30 0 0 23 Oct 2023
Neural Amortized Inference for Nested Multi-agent Reasoning Kunal Jha T. Le Chuanyang Jin Yen-Ling Kuo J. Tenenbaum Tianmin Shu LLMAG AI4CE 15 5 0 21 Aug 2023
Bayesian Program Learning by Decompiling Amortized Knowledge Alessandro B. Palmarini Chris Lucas N. Siddharth CML 6 0 0 13 Jun 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 35 0 0 10 Jun 2023
Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language Kevin Ellis BDL LRM 21 16 0 05 Jun 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 45 4 0 21 Apr 2023
Comparative Study of Coupling and Autoregressive Flows through Robust Statistical Tests A. Coccaro Marco Letizia H. Reyes-González Riccardo Torre OOD 30 5 0 23 Feb 2023
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images Matthew D. Hoffman T. Le Pavel Sountsov Christopher Suter Ben Lee Vikash K. Mansinghka Rif A. Saurous BDL 29 12 0 27 Oct 2022
Uncertain Evidence in Probabilistic Models and Stochastic Simulators Andreas Munk A. Mead Frank D. Wood 17 2 0 21 Oct 2022
Graphically Structured Diffusion Models Christian Weilbach William Harvey Frank D. Wood DiffM 35 7 0 20 Oct 2022
Fast Estimation of Bayesian State Space Models Using Amortized Simulation-Based Inference R. Khabibullin S. Seleznev 28 1 0 13 Oct 2022
Foundation Posteriors for Approximate Probabilistic Inference Mike Wu Noah D. Goodman UQCV 23 6 0 19 May 2022
Recursive Monte Carlo and Variational Inference with Auxiliary Variables Alexander K. Lew Marco F. Cusumano-Towner Vikash K. Mansinghka BDL 16 10 0 05 Mar 2022
Estimators of Entropy and Information via Inference in Probabilistic Models Feras A. Saad Marco F. Cusumano-Towner Vikash K. Mansinghka 9 4 0 24 Feb 2022
Unifying AI Algorithms with Probabilistic Programming using Implicitly Defined Representations Avi Pfeffer M. Harradon Joseph Campolongo S. Cvijic 19 2 0 05 Oct 2021
How To Train Your Program: a Probabilistic Programming Pattern for Bayesian Learning From Data David Tolpin 17 0 0 08 May 2021
Meta-Learning an Inference Algorithm for Probabilistic Programs Gwonsoo Che Hongseok Yang TPM 13 1 0 01 Mar 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 104 185 0 12 Jan 2021
Control-Data Separation and Logical Condition Propagation for Efficient Inference on Probabilistic Programs I. Hasuo Yuichiro Oyabu Clovis Eberhart Kohei Suenaga Kenta Cho Shin-ya Katsumata TPM 22 3 0 05 Jan 2021
Universal Policies for Software-Defined MDPs Daniel Selsam Jesse Michael Han L. D. Moura Patrice Godefroid 17 2 0 21 Dec 2020
Accelerating Metropolis-Hastings with Lightweight Inference Compilation Feynman T. Liang Nimar S. Arora N. Tehrani Y. Li Michael Tingley E. Meijer 12 0 0 23 Oct 2020
Amortized Bayesian Inference for Models of Cognition Stefan T. Radev A. Voss Eva Marie Wieschen Paul-Christian Burkner 6 5 0 08 May 2020
Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices Calypso Herrera Florian Krach Anastasis Kratsios P. Ruyssen Josef Teichmann 28 2 0 28 Apr 2020
Amortized Bayesian model comparison with evidential deep learning Stefan T. Radev Marco D’Alessandro U. Mertens A. Voss Ullrich Kothe Paul-Christian Burkner BDL 20 33 0 22 Apr 2020
Planning as Inference in Epidemiological Models Frank D. Wood Andrew Warrington Saeid Naderiparizi Christian Weilbach Vaden Masrani ... Adam Scibior Boyan Beronov John Grefenstette Duncan Campbell Alireza Nasseri 17 6 0 30 Mar 2020
Coping With Simulators That Don't Always Return Andrew Warrington Saeid Naderiparizi Frank D. Wood 13 4 0 28 Mar 2020
Learning Compositional Rules via Neural Program Synthesis Maxwell Nye Armando Solar-Lezama J. Tenenbaum Brenden Lake NAI LRM 12 117 0 12 Mar 2020
Targeted free energy estimation via learned mappings Peter Wirnsberger A. J. Ballard George Papamakarios Stuart Abercrombie S. Racanière Alexander Pritzel Danilo Jimenez Rezende Charles Blundell 27 86 0 12 Feb 2020
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 24 825 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 29 19 0 29 Oct 2019
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 16 44 0 29 Oct 2019
Attention for Inference Compilation William Harvey Andreas Munk A. G. Baydin Alexander Bergholm Frank D. Wood 17 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 D. Wood TPM 14 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 H. S. Torr Tom Rainforth Yee Whye Teh Frank D. Wood 16 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 12 17 0 17 Oct 2019
Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs R. Walecki Kostis Gourgoulias Adam Baker Chris Hart Chris Lucas Max Zwiessele A. Buchard Maria Lomeli Yura N. Perov Saurabh Johri UQCV 16 0 0 16 Oct 2019
Distilling Importance Sampling for Likelihood Free Inference D. Prangle Cecilia Viscardi 11 3 0 08 Oct 2019
Towards Verified Stochastic Variational Inference for Probabilistic Programs Wonyeol Lee Hangyeol Yu Xavier Rival Hongseok Yang 16 23 0 20 Jul 2019
Amortized Monte Carlo Integration Adam Goliñski Frank D. Wood Tom Rainforth 23 4 0 18 Jul 2019
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale A. G. Baydin Lei Shao W. Bhimji Lukas Heinrich Lawrence Meadows ... Philip H. S. Torr Victor W. Lee Kyle Cranmer P. Prabhat Frank D. Wood 25 55 0 08 Jul 2019
The Thermodynamic Variational Objective Vaden Masrani T. Le Frank D. Wood 14 48 0 28 Jun 2019
Hijacking Malaria Simulators with Probabilistic Programming Bradley Gram-Hansen Christian Schroeder de Witt Tom Rainforth Philip H. S. Torr Yee Whye Teh A. G. Baydin 23 8 0 29 May 2019
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations Niccolò Dalmasso Ann B. Lee Rafael Izbicki T. Pospisil Ilmun Kim Chieh-An Lin 19 8 0 27 May 2019
Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems Ali Malik Mike Wu Vrinda Vasavada Jinpeng Song Madison Coots John C. Mitchell Noah D. Goodman Chris Piech AI4Ed 22 9 0 23 May 2019