Deep Probabilistic Programming

13 January 2017

Dustin Tran

Matthew D. Hoffman

Rif A. Saurous

Papers citing "Deep Probabilistic Programming"

50 / 80 papers shown

Title
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation Bowen Li Zhaoyu Li Qiwei Du Jinqi Luo Wenshan Wang ... Katia P. Sycara Pradeep Kumar Ravikumar Alexander G. Gray X. Si Sebastian A. Scherer AI4CE LRM 81 3 0 01 Nov 2024
Probabilistic Answer Set Programming with Discrete and Continuous Random Variables Damiano Azzolini Fabrizio Riguzzi 13 0 0 30 Sep 2024
Probabilistic Programming with Programmable Variational Inference McCoy R. Becker Alexander K. Lew Xiaoyan Wang Matin Ghavami Mathieu Huot Martin Rinard Vikash K. Mansinghka 45 3 0 22 Jun 2024
Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support Tim Reichelt C.-H. Luke Ong Tom Rainforth 25 0 0 23 Oct 2023
Scalable Neural-Probabilistic Answer Set Programming Arseny Skryagin Daniel Ochs D. Dhami Kristian Kersting 32 5 0 14 Jun 2023
Push: Concurrent Probabilistic Programming for Bayesian Deep Learning Daniel Huang Christian Camaño Jonathan Tsegaye Jonathan Austin Gale AI4CE 30 0 0 10 Jun 2023
Neural Probabilistic Logic Programming in Discrete-Continuous Domains Lennert De Smet Pedro Zuidberg Dos Martires Robin Manhaeve G. Marra Angelika Kimmig Luc de Raedt NAI 11 20 0 08 Mar 2023
Automatically Marginalized MCMC in Probabilistic Programming Jinlin Lai Javier Burroni Hui Guan Daniel Sheldon 21 3 0 01 Feb 2023
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 48 0 14 Nov 2022
PyRelationAL: a python library for active learning research and development P. Scherer Thomas Gaudelet Alison Pouplin Alice Del Vecchio S. SurajM Oliver Bolton Jyothish Soman J. Taylor-King Lindsay Edwards KELM 19 0 0 23 May 2022
Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives J. Warrell M. Gerstein GP 14 1 0 30 Mar 2022
On Reinforcement Learning, Effect Handlers, and the State Monad Ugo Dal Lago Francesco Gavazzo Alexis Ghyselen 16 1 0 29 Mar 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard E. Turner FedML 19 12 0 24 Feb 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 S. Seshia 35 3 0 01 Dec 2021
Toward an Idiomatic Framework for Cognitive Robotics Malte Rørmose Damgaard Rasmus Pedersen T. Bak LM&Ro 11 3 0 25 Nov 2021
Explaining Deep Tractable Probabilistic Models: The sum-product network case Athresh Karanam Saurabh Mathur P. Radivojac David M. Haas Kristian Kersting Sriraam Natarajan FAtt TPM LRM 17 2 0 19 Oct 2021
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling Gianluigi Silvestri Emily Fertig David A. Moore L. Ambrogioni BDL TPM AI4CE 28 3 0 12 Oct 2021
SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming Arseny Skryagin Wolfgang Stammer Daniel Ochs D. Dhami Kristian Kersting NAI 33 6 0 07 Oct 2021
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning Hoifung Poon Hai Wang Hunter Lang SSL 11 2 0 27 Jul 2021
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 32 1,109 0 07 Jul 2021
Variational Inference for Category Recommendation in E-Commerce platforms Ramasubramanian Balasubramanian Venugopal Mani Abhinav Mathur Sushant Kumar Kannan Achan CML DRL 23 1 0 15 Apr 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 20 23 0 15 Mar 2021
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems Martin Mladenov Chih-Wei Hsu Vihan Jain Eugene Ie Christopher Colby Nicolas Mayoraz H. Pham Dustin Tran Ivan Vendrov Craig Boutilier BDL 13 31 0 14 Mar 2021
Automatic variational inference with cascading flows L. Ambrogioni Gianluigi Silvestri Marcel van Gerven TPM BDL 19 8 0 09 Feb 2021
On Variational Inference for User Modeling in Attribute-Driven Collaborative Filtering Venugopal Mani Ramasubramanian Balasubramanian Sushant Kumar Abhinav Mathur Kannan Achan CML BDL EgoV 11 1 0 02 Dec 2020
Analysis of Bayesian Networks via Prob-Solvable Loops E. Bartocci L. Kovács Miroslav Stankovič TPM 8 12 0 18 Jul 2020
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users Laurent Valentin Jospin Wray L. Buntine F. Boussaïd Hamid Laga Bennamoun OOD BDL UQCV 11 608 0 14 Jul 2020
Efficient Computation Reduction in Bayesian Neural Networks Through Feature Decomposition and Memorization Xiaotao Jia Jianlei Yang Runze Liu Xueyan Wang S. Cotofana Weisheng Zhao 11 26 0 08 May 2020
Scaling Bayesian inference of mixed multinomial logit models to very large datasets Filipe Rodrigues BDL 14 3 0 11 Apr 2020
A Differential-form Pullback Programming Language for Higher-order Reverse-mode Automatic Differentiation Carol Mak C.-H. Luke Ong 11 10 0 19 Feb 2020
Lazy object copy as a platform for population-based probabilistic programming Lawrence M. Murray 16 5 0 09 Jan 2020
Probabilistic Software Modeling: A Data-driven Paradigm for Software Analysis Hannes Thaller L. Linsbauer Rudolf Ramler Alexander Egyed 23 3 0 17 Dec 2019
A probabilistic assessment of the Indo-Aryan Inner-Outer Hypothesis C. Cathcart 11 15 0 29 Nov 2019
Estimating uncertainty of earthquake rupture using Bayesian neural network S. Ahamed Md Mesbah Uddin 11 5 0 21 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 18 19 0 29 Oct 2019
BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat Brian Karrer Daniel R. Jiang Sam Daulton Benjamin Letham A. Wilson E. Bakshy 19 93 0 14 Oct 2019
Unconstrained Monotonic Neural Networks Antoine Wehenkel Gilles Louppe TPM 26 146 0 14 Aug 2019
Transcriptional Response of SK-N-AS Cells to Methamidophos A. Vertes Albert-Baskar Arul P. Avar Andrew R. Korte Lida Parvin ... C. Talcott Brian M. Davis Christine A. Morton Christopher J. Sevinsky M. Zavodszky 11 1 0 11 Aug 2019
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling Feras A. Saad Marco F. Cusumano-Towner Ulrich Schaechtle Martin Rinard Vikash K. Mansinghka 17 58 0 14 Jul 2019
On Open-Universe Causal Reasoning D. Ibeling Thomas F. Icard LRM AI4CE 18 8 0 04 Jul 2019
Hyper-Molecules: on the Representation and Recovery of Dynamical Structures, with Application to Flexible Macro-Molecular Structures in Cryo-EM Roy R. Lederman Joakim Andén A. Singer 21 31 0 02 Jul 2019
GPU-based Parallel Computation Support for Stan Rok Cesnovar S. Bronder Davor Sluga J. Demšar Tadej Ciglarič Sean Talts Erik Štrumbelj 11 4 0 01 Jul 2019
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks Qi She Anqi Wu BDL 18 34 0 01 Jul 2019
Deployable probabilistic programming David Tolpin TPM 22 7 0 20 Jun 2019
An Introduction to Variational Autoencoders Diederik P. Kingma Max Welling BDL SSL DRL 33 2,285 0 06 Jun 2019
Coupled VAE: Improved Accuracy and Robustness of a Variational Autoencoder Shichen Cao Jingjing Li Kenric P. Nelson Mark A. Kon BDL DRL 14 15 0 03 Jun 2019
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records Linying Zhang Yixin Wang A. Ostropolets J. J. Mulgrave David M. Blei G. Hripcsak BDL CML 13 1 0 03 Apr 2019
LYRICS: a General Interface Layer to Integrate Logic Inference and Deep Learning G. Marra Francesco Giannini Michelangelo Diligenti Marco Gori AI4CE 24 11 0 18 Mar 2019
Applying Probabilistic Programming to Affective Computing Desmond C. Ong Harold Soh Jamil Zaki Noah D. Goodman 11 20 0 15 Mar 2019
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models Yuanshuo Zhou Bradley Gram-Hansen Tobias Kohn Tom Rainforth Hongseok Yang Frank D. Wood 23 24 0 06 Mar 2019