Deep Probabilistic Programming

13 January 2017

Dustin Tran

Matthew D. Hoffman

Rif A. Saurous

Papers citing "Deep Probabilistic Programming"

30 / 80 papers shown

Title
A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory Networks Cassandra Burdziak E. Azizi Sandhya Prabhakaran D. Pe’er 14 14 0 21 Feb 2019
ProBO: Versatile Bayesian Optimization Using Any Probabilistic Programming Language W. Neiswanger Kirthevasan Kandasamy Barnabás Póczós J. Schneider Eric P. Xing 28 17 0 31 Jan 2019
Doubly Bayesian Optimization Alexander Lavin 28 0 0 11 Dec 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 19 55 0 27 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 22 56 0 05 Nov 2018
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 15 1,030 0 18 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 11 4 0 30 Sep 2018
An Introduction to Probabilistic Programming Jan-Willem van de Meent Brooks Paige Hongseok Yang Frank D. Wood GP 15 196 0 27 Sep 2018
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model A. G. Baydin Lukas Heinrich W. Bhimji Lei Shao Saeid Naderiparizi ... Philip Torr Victor W. Lee P. Prabhat Kyle Cranmer Frank D. Wood 26 31 0 20 Jul 2018
Machine Learning in High Energy Physics Community White Paper K. Albertsson Piero Altoe D. Anderson John R. Anderson Michael Andrews ... Michael Williams Wenjing Wu Stefan Wunsch Kun Yang O. Zapata AI4CE 11 220 0 08 Jul 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 38 180 0 30 May 2018
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow T. Le Adam R. Kosiorek N. Siddharth Yee Whye Teh Frank D. Wood BDL 9 23 0 26 May 2018
Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming Kirthevasan Kandasamy W. Neiswanger Reed Zhang A. Krishnamurthy J. Schneider Barnabás Póczós 14 5 0 25 May 2018
The Blessings of Multiple Causes Yixin Wang David M. Blei AI4CE CML 24 284 0 17 May 2018
Improving Predictive Uncertainty Estimation using Dropout -- Hamiltonian Monte Carlo Diego Vergara S. Hernández Matias Valdenegro-Toro Felipe Jorquera UQCV BDL 19 0 0 12 May 2018
Deep Probabilistic Programming Languages: A Qualitative Study Guillaume Baudart Martin Hirzel Louis Mandel UQCV TPM 13 8 0 17 Apr 2018
Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities Bradley Gram-Hansen Yuanshuo Zhou Tobias Kohn Tom Rainforth Hongseok Yang Frank D. Wood 16 3 0 07 Apr 2018
Stochastic Variational Inference with Gradient Linearization Tobias Plötz Anne S. Wannenwetsch Stefan Roth 6 2 0 28 Mar 2018
Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs Forough Arabshahi Sameer Singh Anima Anandkumar NAI 8 5 0 12 Jan 2018
Towards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathology Andreas Holzinger Bernd Malle Peter Kieseberg P. Roth Heimo Muller Robert Reihs K. Zatloukal 17 91 0 18 Dec 2017
Variational Deep Q Network Yunhao Tang A. Kucukelbir BDL 38 10 0 30 Nov 2017
TensorFlow Distributions Joshua V. Dillon I. Langmore Dustin Tran E. Brevdo Srinivas Vasudevan David A. Moore Brian Patton Alexander A. Alemi Matt Hoffman Rif A. Saurous GP 44 346 0 28 Nov 2017
Programmable Agents Misha Denil Sergio Gomez Colmenarejo Serkan Cabi D. Saxton Nando de Freitas AI4CE 20 42 0 20 Jun 2017
Deep Learning for Spatio-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading M. Dixon Nicholas G. Polson Vadim Sokolov AI4TS 25 67 0 27 May 2017
Reducing Reparameterization Gradient Variance Andrew C. Miller N. Foti Alexander DÁmour Ryan P. Adams 22 84 0 22 May 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 104 1,502 0 25 Jan 2017
Variational Inference via $χ$ -Upper Bound Minimization Adji Bousso Dieng Dustin Tran Rajesh Ranganath John Paisley David M. Blei BDL 81 36 0 01 Nov 2016
Differentially Private Variational Inference for Non-conjugate Models Joonas Jälkö O. Dikmen Antti Honkela FedML 21 48 0 27 Oct 2016
Scene Grammars, Factor Graphs, and Belief Propagation Jeroen Chua Pedro F. Felzenszwalb 3DV 13 9 0 03 Jun 2016
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 54 2,746 0 20 Feb 2015