Venture: a higher-order probabilistic programming platform with programmable inference

1 April 2014

Papers citing "Venture: a higher-order probabilistic programming platform with programmable inference"

50 / 99 papers shown

Title
Probabilistic Programming with Programmable Variational Inference McCoy R. Becker Alexander K. Lew Xiaoyan Wang Matin Ghavami Mathieu Huot Martin Rinard Vikash K. Mansinghka 126 5 0 22 Jun 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
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
ADEV: Sound Automatic Differentiation of Expected Values of Probabilistic Programs Alexander K. Lew Mathieu Huot S. Staton Vikash K. Mansinghka 59 22 0 13 Dec 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
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference Wonyeol Lee Xavier Rival Hongseok Yang 96 10 0 22 Aug 2022
Foundation Posteriors for Approximate Probabilistic Inference Mike Wu Noah D. Goodman UQCV 94 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 60 11 0 05 Mar 2022
Toward an Idiomatic Framework for Cognitive Robotics Malte Rørmose Damgaard Rasmus Pedersen T. Bak LM&Ro 72 3 0 25 Nov 2021
Unifying AI Algorithms with Probabilistic Programming using Implicitly Defined Representations Avi Pfeffer M. Harradon Joseph Campolongo S. Cvijic 46 2 0 05 Oct 2021
DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in Deep Learning Hossein Rajaby Faghihi Quan Guo Andrzej Uszok Aliakbar Nafar Elaheh Raisi Parisa Kordjamshidi AI4CE 66 18 0 27 Aug 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
SBI: A Simulation-Based Test of Identifiability for Bayesian Causal Inference Sam Witty David D. Jensen Vikash K. Mansinghka CML 71 3 0 23 Feb 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 43 3 0 05 Jan 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
PPL Bench: Evaluation Framework For Probabilistic Programming Languages S. Kulkarni K. Shah Nimar S. Arora Xiaoyang Sean Wang Y. Li ... David Noursi Narjes Torabi Sepehr Akhavan Masouleh Eric Lippert E. Meijer 8 2 0 17 Oct 2020
Neuro-symbolic Neurodegenerative Disease Modeling as Probabilistic Programmed Deep Kernels Alexander Lavin BDL MedIm 79 9 0 16 Sep 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
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
Lazy object copy as a platform for population-based probabilistic programming Lawrence M. Murray 51 5 0 09 Jan 2020
Parameter elimination in particle Gibbs sampling A. Wigren Riccardo Sven Risuleo Lawrence M. Murray Fredrik Lindsten 83 15 0 30 Oct 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
Particle filter with rejection control and unbiased estimator of the marginal likelihood J. Kudlicka Lawrence M. Murray Thomas B. Schon Fredrik Lindsten 115 2 0 21 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
Population Predictive Checks Rajesh Ranganath David M. Blei Rajesh Ranganath 66 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
Probabilistic programming for birth-death models of evolution using an alive particle filter with delayed sampling J. Kudlicka Lawrence M. Murray F. Ronquist Thomas B. Schon 63 10 0 10 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
ProBO: Versatile Bayesian Optimization Using Any Probabilistic Programming Language Willie Neiswanger Kirthevasan Kandasamy Barnabás Póczós J. Schneider Eric Xing 94 18 0 31 Jan 2019
Soft Constraints for Inference with Declarative Knowledge Zenna Tavares Javier Burroni Edgar Minaysan Armando Solar-Lezama Rajesh Ranganath 46 2 0 16 Jan 2019
Doubly Bayesian Optimization Alexander Lavin 38 0 0 11 Dec 2018
Nested Reasoning About Autonomous Agents Using Probabilistic Programs I. Seaman Jan-Willem van de Meent David Wingate LRM 83 13 0 04 Dec 2018
Composing Modeling and Inference Operations with Probabilistic Program Combinators Eli Sennesh Adam Scibior Hao Wu Jan-Willem van de Meent TPM 29 1 0 14 Nov 2018
Simple, Distributed, and Accelerated Probabilistic Programming Like Hui Matthew Hoffman Siyuan Ma Christopher Suter Srinivas Vasudevan Alexey Radul M. Belkin Rif A. Saurous BDL 85 56 0 05 Nov 2018
Probabilistic Programming with Densities in SlicStan: Efficient, Flexible and Deterministic Maria I. Gorinova Andrew D. Gordon Charles Sutton 77 24 0 02 Nov 2018
Automated learning with a probabilistic programming language: Birch Lawrence M. Murray Thomas B. Schon 76 63 0 02 Oct 2018
Inference Over Programs That Make Predictions Yura N. Perov 35 2 0 02 Oct 2018
Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming Guillaume Baudart Javier Burroni Martin Hirzel Louis Mandel Avraham Shinnar BDL 40 4 0 30 Sep 2018