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Uncertainty in Neural Processes

Oct 08, 2020
Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy, Frank Wood


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Assisting the Adversary to Improve GAN Training

Oct 03, 2020
Andreas Munk, William Harvey, Frank Wood


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All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference

Jul 01, 2020
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan

* ICML 2020 

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Semi-supervised Sequential Generative Models

Jun 30, 2020
Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood

* Accepted to Uncertainty in Artificial Intelligence 2020 

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Improving Few-Shot Visual Classification with Unlabelled Examples

Jun 17, 2020
Peyman Bateni, Jarred Barber, Jan-Willem van de Meent, Frank Wood


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Planning as Inference in Epidemiological Models

Apr 03, 2020
Frank Wood, Andrew Warrington, Saeid Naderiparizi, Christian Weilbach, Vaden Masrani, William Harvey, Adam Scibior, Boyan Beronov, Ali Nasseri

* minor typos corrected 

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Coping With Simulators That Don't Always Return

Mar 28, 2020
Andrew Warrington, Saeid Naderiparizi, Frank Wood

* AISTATS 2020 camera ready, version 1.0 

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Improved Few-Shot Visual Classification

Dec 12, 2019
Peyman Bateni, Raghav Goyal, Vaden Masrani, Frank Wood, Leonid Sigal


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Amortized Rejection Sampling in Universal Probabilistic Programming

Nov 30, 2019
Saeid Naderiparizi, Adam Ścibior, Andreas Munk, Mehrdad Ghadiri, Atılım Güneş Baydin, Bradley Gram-Hansen, Christian Schroeder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood


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Attention for Inference Compilation

Oct 25, 2019
William Harvey, Andreas Munk, Atılım Güneş Baydin, Alexander Bergholm, Frank Wood


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Deep Probabilistic Surrogate Networks for Universal Simulator Approximation

Oct 25, 2019
Andreas Munk, Adam Ścibior, Atılım Güneş Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood


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Safer End-to-End Autonomous Driving via Conditional Imitation Learning and Command Augmentation

Sep 20, 2019
Renhao Wang, Adam Scibior, Frank Wood

* Submitted to the 2020 International Conference on Robotics and Automation 

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The Virtual Patch Clamp: Imputing C. elegans Membrane Potentials from Calcium Imaging

Jul 24, 2019
Andrew Warrington, Arthur Spencer, Frank Wood

* Includes Supplementary Materials 

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Amortized Monte Carlo Integration

Jul 18, 2019
Adam Goliński, Frank Wood, Tom Rainforth

* Awarded Best Paper Honourable Mention at International Conference on Machine Learning (ICML) 2019 

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Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

Jul 08, 2019
Atılım Güneş Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip Torr, Victor Lee, Kyle Cranmer, Prabhat, Frank Wood

* 14 pages, 8 figures 

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The Thermodynamic Variational Objective

Jun 28, 2019
Vaden Masrani, Tuan Anh Le, Frank Wood


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Near-Optimal Glimpse Sequences for Improved Hard Attention Neural Network Training

Jun 13, 2019
William Harvey, Michael Teng, Frank Wood

* 9 pages, 5 figures + appendix with 6 pages, 4 figures.Submitted to NeurIPS 2019 

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Imitation Learning of Factored Multi-agent Reactive Models

Mar 12, 2019
Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood


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LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models

Mar 06, 2019
Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood

* Published in the proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 

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Faithful Inversion of Generative Models for Effective Amortized Inference

Oct 24, 2018
Stefan Webb, Adam Golinski, Robert Zinkov, N. Siddharth, Tom Rainforth, Yee Whye Teh, Frank Wood

* To appear at the 32nd Conference on Neural Information Processing Systems (NIPS 2018), Montreal, Canada 

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An Introduction to Probabilistic Programming

Sep 27, 2018
Jan-Willem van de Meent, Brooks Paige, Hongseok Yang, Frank Wood

* Under review at Foundations and Trends in Machine Learning 

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Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model

Sep 01, 2018
Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank Wood

* 18 pages, 5 figures 

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Tighter Variational Bounds are Not Necessarily Better

Jun 25, 2018
Tom Rainforth, Adam R. Kosiorek, Tuan Anh Le, Chris J. Maddison, Maximilian Igl, Frank Wood, Yee Whye Teh

* To appear at ICML 2018 

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Inference Trees: Adaptive Inference with Exploration

Jun 25, 2018
Tom Rainforth, Yuan Zhou, Xiaoyu Lu, Yee Whye Teh, Frank Wood, Hongseok Yang, Jan-Willem van de Meent


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Deep Variational Reinforcement Learning for POMDPs

Jun 06, 2018
Maximilian Igl, Luisa Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson


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Revisiting Reweighted Wake-Sleep

May 26, 2018
Tuan Anh Le, Adam R. Kosiorek, N. Siddharth, Yee Whye Teh, Frank Wood

* Tuan Anh Le and Adam R. Kosiorek contributed equally 

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On Nesting Monte Carlo Estimators

May 23, 2018
Tom Rainforth, Robert Cornish, Hongseok Yang, Andrew Warrington, Frank Wood

* To appear at International Conference on Machine Learning 2018 

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