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Church: a language for generative models

13 June 2012

Papers citing "Church: a language for generative models"

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Title
SatelliteFormula: Multi-Modal Symbolic Regression from Remote Sensing Imagery for Physics Discovery Zhenyu Yu Mohd Yamani Idna Idris Pei Wang Yuelong Xia Fei Ma Rizwan Qureshi 40 0 0 06 Jun 2025
LLM-Guided Probabilistic Program Induction for POMDP Model Estimation Aidan Curtis Hao Tang Thiago Veloso Kevin Ellis Joshua B. Tenenbaum Tomás Lozano-Pérez Leslie Pack Kaelbling 397 1 0 04 May 2025
A Distribution Semantics for Probabilistic Term Rewriting Germán Vidal 79 0 0 19 Oct 2024
Building Machines that Learn and Think with People Katherine M. Collins Ilia Sucholutsky Umang Bhatt Kartik Chandra Lionel Wong ... Mark K. Ho Vikash K. Mansinghka Adrian Weller Joshua B. Tenenbaum Thomas Griffiths 133 38 0 22 Jul 2024
Element-Free Probability Distributions and Random Partitions Victor Blanchi Hugo Paquet 29 1 0 27 May 2024
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems David Dalrymple Joar Skalse Yoshua Bengio Stuart J. Russell Max Tegmark ... Clark Barrett Ding Zhao Zhi-Xuan Tan Jeannette Wing Joshua Tenenbaum 130 62 0 10 May 2024
Foundation Model Sherpas: Guiding Foundation Models through Knowledge and Reasoning D. Bhattacharjya Junkyu Lee Don Joven Agravante Balaji Ganesan Radu Marinescu LLMAG 50 1 0 02 Feb 2024
Recovering Mental Representations from Large Language Models with Markov Chain Monte Carlo Jian-Qiao Zhu Haijiang Yan Thomas Griffiths 48 3 0 30 Jan 2024
Exploring the hierarchical structure of human plans via program generation Carlos G. Correa Sophia Sanborn Mark K. Ho Frederick Callaway Nathaniel D. Daw Thomas Griffiths 70 11 0 30 Nov 2023
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support Tim Reichelt C. Ong Tom Rainforth 61 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
Worst-Case Analysis is Maximum-A-Posteriori Estimation Hongjun Wu Di Wang 41 0 0 15 Oct 2023
A Heavy-Tailed Algebra for Probabilistic Programming Feynman T. Liang Liam Hodgkinson Michael W. Mahoney 67 3 0 15 Jun 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
Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language Kevin Ellis BDL LRM 68 16 0 05 Jun 2023
Evaluating statistical language models as pragmatic reasoners Benjamin Lipkin L. Wong Gabriel Grand J. Tenenbaum 133 15 0 01 May 2023
Meta-Learned Models of Cognition Marcel Binz Ishita Dasgupta Akshay K. Jagadish M. Botvinick Jane X. Wang Eric Schulz 94 27 0 12 Apr 2023
Declarative Probabilistic Logic Programming in Discrete-Continuous Domains Pedro Zuidberg Dos Martires Luc de Raedt Angelika Kimmig 94 4 0 21 Feb 2023
Thermodynamic AI and the fluctuation frontier Patrick J. Coles Collin Szczepanski Denis Melanson Kaelan Donatella Antonio J. Martinez Faris M. Sbahi AI4CE 77 19 0 09 Feb 2023
Counterfactual Identifiability of Bijective Causal Models Arash Nasr-Esfahany MohammadIman Alizadeh Devavrat Shah CML BDL 113 27 0 04 Feb 2023
Automatically Marginalized MCMC in Probabilistic Programming Jinlin Lai Javier Burroni Hui Guan Daniel Sheldon 80 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
Swift Markov Logic for Probabilistic Reasoning on Knowledge Graphs Luigi Bellomarini Eleonora Laurenza Emanuel Sallinger Evgeny Sherkhonov 47 0 0 01 Oct 2022
Dr. Neurosymbolic, or: How I Learned to Stop Worrying and Accept Statistics Masataro Asai 75 0 0 08 Sep 2022
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference Wonyeol Lee Xavier Rival Hongseok Yang 96 10 0 22 Aug 2022
Tensor Program Optimization with Probabilistic Programs Junru Shao Xiyou Zhou Siyuan Feng Bohan Hou Ruihang Lai Hongyi Jin Wuwei Lin Masahiro Masuda Cody Hao Yu Tianqi Chen 85 31 0 26 May 2022
Foundation Posteriors for Approximate Probabilistic Inference Mike Wu Noah D. Goodman UQCV 94 6 0 19 May 2022
Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming Raven Beutner Luke Ong Fabian Zaiser 62 12 0 06 Apr 2022
Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives J. Warrell M. Gerstein GP 49 1 0 30 Mar 2022
Mixed Nondeterministic-Probabilistic Automata: Blending graphical probabilistic models with nondeterminism A. Benveniste Jean-Baptiste Raclet TPM 47 1 0 19 Jan 2022
Programming with Neural Surrogates of Programs Alex Renda Yi Ding Michael Carbin 36 4 0 12 Dec 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
Supervised Bayesian Specification Inference from Demonstrations Ankit J. Shah Pritish Kamath Shen Li Patrick L. Craven Kevin J. Landers Kevin B. Oden J. Shah 122 3 0 06 Jul 2021
Nonparametric Hamiltonian Monte Carlo Carol Mak Fabian Zaiser C.-H. Luke Ong 58 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
A Whole Brain Probabilistic Generative Model: Toward Realizing Cognitive Architectures for Developmental Robots T. Taniguchi Hiroshi Yamakawa Takayuki Nagai Kenji Doya M. Sakagami Masahiro Suzuki Tomoaki Nakamura Akira Taniguchi 72 24 0 15 Mar 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
Automatic variational inference with cascading flows L. Ambrogioni Gianluigi Silvestri Marcel van Gerven TPM BDL 46 10 0 09 Feb 2021
Universal Policies for Software-Defined MDPs Daniel Selsam Jesse Michael Han L. D. Moura Patrice Godefroid 47 2 0 21 Dec 2020
Modeling Content and Context with Deep Relational Learning Maria Leonor Pacheco Dan Goldwasser NAI 105 34 0 20 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
Automating Involutive MCMC using Probabilistic and Differentiable Programming Marco F. Cusumano-Towner Alexander K. Lew Vikash K. Mansinghka 74 17 0 20 Jul 2020
Smart Choices and the Selection Monad M. Abadi G. Plotkin 79 4 0 17 Jul 2020
Symbolic Logic meets Machine Learning: A Brief Survey in Infinite Domains Vaishak Belle NAI LRM 108 36 0 15 Jun 2020
Simulation-Based Inference for Global Health Decisions Christian Schroeder de Witt Bradley Gram-Hansen Nantas Nardelli Andrew Gambardella R. Zinkov ... N. Siddharth A. B. Espinosa-González A. Darzi Philip Torr A. G. Baydin AI4CE 61 5 0 14 May 2020
Stochastically Differentiable Probabilistic Programs David Tolpin Yuanshuo Zhou Hongseok Yang BDL 37 0 0 02 Mar 2020