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Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.

W. Jitkrittum, A. Gretton, N. Heess, S. Eslami, B. Lakshminarayanan, D. Sejdinovic, and Z. Szabó. UAI, page 405-414. AUAI Press, (2015)

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Dirk Heeß

Wilhelm Heeß

Walter Heess

Monika Heess

Reiner Heeß

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FeUdal Networks for Hierarchical Reinforcement Learning.A. Vezhnevets, S. Osindero, T. Schaul, N. Heess, M. Jaderberg, D. Silver, and K. Kavukcuoglu. ICML, volume 70 of Proceedings of Machine Learning Research, page 3540-3549. PMLR, (2017)The Termination Critic.A. Harutyunyan, W. Dabney, D. Borsa, N. Heess, R. Munos, and D. Precup. AISTATS, volume 89 of Proceedings of Machine Learning Research, page 2231-2240. PMLR, (2019)Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures.J. Uesato, A. Kumar, C. Szepesvári, T. Erez, A. Ruderman, K. Anderson, K. Dvijotham, N. Heess, and P. Kohli. ICLR (Poster), OpenReview.net, (2019)Neural Probabilistic Motor Primitives for Humanoid Control.J. Merel, L. Hasenclever, A. Galashov, A. Ahuja, V. Pham, G. Wayne, Y. Teh, and N. Heess. ICLR (Poster), OpenReview.net, (2019)Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces.G. Lorberbom, C. Maddison, N. Heess, T. Hazan, and D. Tarlow. CoRR, (2019)Value constrained model-free continuous control.S. Bohez, A. Abdolmaleki, M. Neunert, J. Buchli, N. Heess, and R. Hadsell. CoRR, (2019)Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions.L. Buesing, N. Heess, and T. Weber. CoRR, (2019)Reusable neural skill embeddings for vision-guided whole body movement and object manipulation.J. Merel, S. Tunyasuvunakool, A. Ahuja, Y. Tassa, L. Hasenclever, V. Pham, T. Erez, G. Wayne, and N. Heess. CoRR, (2019)Learning a Generative Model of Images by Factoring Appearance and Shape.N. Roux, N. Heess, J. Shotton, and J. Winn. Neural Comput., 23 (3): 593-650 (2011)Physically Embedded Planning Problems: New Challenges for Reinforcement Learning.M. Mirza, A. Jaegle, J. Hunt, A. Guez, S. Tunyasuvunakool, A. Muldal, T. Weber, P. Karkus, S. Racanière, L. Buesing and 2 other author(s). CoRR, (2020)

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Disambiguation of "Heess, Nicolas"

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Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.

Please choose a person to relate this publication to

Dirk Heeß

Wilhelm Heeß

Walter Heess

Monika Heess

Reiner Heeß

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Heess, Nicolas"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.

Please choose a person to relate this publication to

Dirk Heeß

Wilhelm Heeß

Walter Heess

Monika Heess

Reiner Heeß

Other publications of authors with the same name

Disambiguation

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URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.