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All publications by Nicolas Heess
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Gradient Estimation Using Stochastic Computation Graphs
John Schulman, Nicolas Heess, Theophane Weber and Pieter Abbeel
Advances in Neural Information Processing Systems 28, 2015


Learning Continuous Control Policies by Stochastic Value Gradients
Nicolas Heess, Gregory Wayne, David Silver, Tim Lillicrap, Tom Erez and Yuval Tassa
Advances in Neural Information Processing Systems 28, 2015


Deterministic Policy Gradient Algorithms
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra and Martin Riedmiller
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Recurrent Models of Visual Attention
Volodymyr Mnih, Nicolas Heess, Alex Graves and Koray Kavukcuoglu
Advances in Neural Information Processing Systems 27, 2014


Bayes-Adaptive Simulation-based Search with Value Function Approximation
Arthur Guez, Nicolas Heess, David Silver and Peter Dayan
Advances in Neural Information Processing Systems 27, 2014


Learning to Pass Expectation Propagation Messages
Nicolas Heess, Daniel Tarlow and John Winn
Advances in Neural Information Processing Systems 26, 2013


Searching for objects driven by context
Bogdan Alexe, Nicolas Heess, Yee W. Teh and Vittorio Ferrari
Advances in Neural Information Processing Systems 25, 2012