Tuan Anh Le

According to our database, Tuan Anh Le authored at least 21 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Neural Amortized Inference for Nested Multi-Agent Reasoning.

Kunal Jha, Tuan Anh Le, Chuanyang Jin, Yen-Ling Kuo, Joshua B. Tenenbaum, Tianmin Shu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2022

Drawing out of Distribution with Neuro-Symbolic Generative Models.

Yichao Liang, Josh Tenenbaum, Tuan Anh Le, N. Siddharth

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface.

Tuan Anh Le, Katherine M. Collins, Luke Hewitt, Kevin Ellis, Siddharth Narayanaswamy, Samuel Gershman, Joshua B. Tenenbaum

Proceedings of the Tenth International Conference on Learning Representations, 2022

Benchmarking mid-level vision with texture-defined 3D objects.

Yoni Friedman, Thomas P. O'Connell, Max H. Siegel, Daniel M. Bear, Tuan Anh Le, Bernhard Egger, Josh Tenenbaum

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

2021

Explaining the Gestalt principle of common fate as amortized inference.

Yoni Friedman, Tuan Anh Le, Bernhard Egger, Max H. Siegel, Josh Tenenbaum

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

Learning Evolved Combinatorial Symbols with a Neuro-symbolic Generative Model.

Matthias Hofer, Tuan Anh Le, Roger Levy, Josh Tenenbaum

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

Amortized inference and model learning for probabilistic programming.

Tuan Anh Le

PhD thesis, 2020

Semi-supervised Sequential Generative Models.

Michael Teng, Tuan Anh Le, Adam Scibior, Frank Wood

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Learning to learn generative programs with Memoised Wake-Sleep.

Luke B. Hewitt, Tuan Anh Le, Joshua B. Tenenbaum

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Amortized Population Gibbs Samplers with Neural Sufficient Statistics.

Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow.

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

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

The Thermodynamic Variational Objective.

Vaden Masrani, Tuan Anh Le, Frank Wood

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Revisiting Reweighted Wake-Sleep.

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

CoRR, 2018

Tighter Variational Bounds are Not Necessarily Better.

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

Proceedings of the 35th International Conference on Machine Learning, 2018

Deep Variational Reinforcement Learning for POMDPs.

Maximilian Igl, Luisa M. Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson

Proceedings of the 35th International Conference on Machine Learning, 2018

Auto-Encoding Sequential Monte Carlo.

Tuan Anh Le, Maximilian Igl, Tom Rainforth, Tom Jin, Frank Wood

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators.

Mario Lezcano Casado, Atilim Gunes Baydin, David Martínez-Rubio, Tuan Anh Le, Frank D. Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji, Prabhat

CoRR, 2017

Using synthetic data to train neural networks is model-based reasoning.

Tuan Anh Le, Atilim Günes Baydin, Robert Zinkov, Frank D. Wood

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Inference Compilation and Universal Probabilistic Programming.

Tuan Anh Le, Atilim Gunes Baydin, Frank D. Wood

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Bayesian Optimization for Probabilistic Programs.

Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, Frank D. Wood

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Data-driven Sequential Monte Carlo in Probabilistic Programming.

Yura N. Perov, Tuan Anh Le, Frank D. Wood

CoRR, 2015