Articles with public access mandates - Tuan Anh LeLearn more
Available somewhere: 9
Deep variational reinforcement learning for POMDPs
M Igl, L Zintgraf, TA Le, F Wood, S Whiteson
International Conference on Machine Learning, 2117-2126, 2018
Mandates: US Department of Defense, UK Engineering and Physical Sciences Research …
Tighter Variational Bounds are Not Necessarily Better
T Rainforth, AR Kosiorek, TA Le, CJ Maddison, M Igl, F Wood, YW Teh
International Conference on Machine Learning, 2018
Mandates: US Department of Defense, UK Engineering and Physical Sciences Research …
Inference Compilation and Universal Probabilistic Programming
TA Le, AG Baydin, F Wood
20th International Conference on Artificial Intelligence and Statistics 54 …, 2017
Mandates: US Department of Defense, UK Engineering and Physical Sciences Research Council
Using Synthetic Data to Train Neural Networks is Model-Based Reasoning
TA Le, AG Baydin, R Zinkov, F Wood
30th International Joint Conference on Neural Networks, 3514--3521, 2017
Mandates: US Department of Defense, UK Engineering and Physical Sciences Research Council
Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow
TA Le, AR Kosiorek, N Siddharth, YW Teh, F Wood
Proc. of the Conf. on Uncertainty in AI (UAI), 2019
Mandates: US Department of Defense, UK Engineering and Physical Sciences Research …
The Thermodynamic Variational Objective
V Masrani, TA Le, F Wood
Advances in Neural Information Processing Systems, 11525-11534, 2019
Mandates: US Department of Defense, Natural Sciences and Engineering Research Council …
Learning to learn generative programs with Memoised Wake-Sleep
LB Hewitt, TA Le, JB Tenenbaum
Uncertainty in Artificial Intelligence, 2020
Mandates: US Department of Defense
Drawing out of Distribution with Neuro-Symbolic Generative Models
Y Liang, JB Tenenbaum, TA Le, N Siddharth
Advances in Neural Information Processing Systems, 2022
Mandates: UK Engineering and Physical Sciences Research Council
Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators
ML Casado, AG Baydin, DM Rubio, TA Le, F Wood, L Heinrich, G Louppe, ...
NIPS Workshop on Deep Learning for Physical Sciences, 2017
Mandates: US National Science Foundation, US Department of Energy, US Department of …
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