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Understanding Self-Predictive Learning for Reinforcement Learning.

Y. Tang, Z. Guo, P. Richemond, B. Pires, Y. Chandak, R. Munos, M. Rowland, M. Azar, C. Lan, C. Lyle, A. György, S. Thakoor, W. Dabney, B. Piot, D. Calandriello, and M. Valko. ICML, volume 202 of Proceedings of Machine Learning Research, page 33632-33656. PMLR, (2023)

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Christoper Lyle

John Lyle

Allan Lyle

Bernd Claren

Hildegard Clarenz-Löhnert

Other publications of authors with the same name

On the Benefits of Invariance in Neural Networks.C. Lyle, M. van der Wilk, M. Kwiatkowska, Y. Gal, and B. Bloem-Reddy. CoRR, (2020)The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation.M. Brundage, S. Avin, J. Clark, H. Toner, P. Eckersley, B. Garfinkel, A. Dafoe, P. Scharre, T. Zeitzoff, B. Filar and 16 other author(s). CoRR, (2018)A Geometric Perspective on Optimal Representations for Reinforcement Learning.M. Bellemare, W. Dabney, R. Dadashi, A. Taïga, P. Castro, N. Roux, D. Schuurmans, T. Lattimore, and C. Lyle. NeurIPS, page 4360-4371. (2019)Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning.J. Kossen, N. Band, C. Lyle, A. Gomez, T. Rainforth, and Y. Gal. NeurIPS, page 28742-28756. (2021)The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation.M. Rowland, Y. Tang, C. Lyle, R. Munos, M. Bellemare, and W. Dabney. ICML, volume 202 of Proceedings of Machine Learning Research, page 29210-29231. PMLR, (2023)Understanding Self-Predictive Learning for Reinforcement Learning.Y. Tang, Z. Guo, P. Richemond, B. Pires, Y. Chandak, R. Munos, M. Rowland, M. Azar, C. Lan, C. Lyle and 6 other author(s). ICML, volume 202 of Proceedings of Machine Learning Research, page 33632-33656. PMLR, (2023)Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning.A. Kirsch, C. Lyle, and Y. Gal. CoRR, (2020)Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model.M. Rowland, L. Wenliang, R. Munos, C. Lyle, Y. Tang, and W. Dabney. CoRR, (2024)Mixtures of Experts Unlock Parameter Scaling for Deep RL.J. Obando-Ceron, G. Sokar, T. Willi, C. Lyle, J. Farebrother, J. Foerster, G. Dziugaite, D. Precup, and P. Castro. CoRR, (2024)Some Counterexamples for Compatible Triangulations.C. Barnson, D. Chandler, Q. Chen, C. Chung, A. Coccimiglio, S. La, L. Li, A. Linn, A. Lubiw, C. Lyle and 6 other author(s). CoRR, (2016)

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Disambiguation of "Lyle, Clare"

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Understanding Self-Predictive Learning for Reinforcement Learning.

Please choose a person to relate this publication to

Christoper Lyle

John Lyle

Allan Lyle

Bernd Claren

Hildegard Clarenz-Löhnert

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Lyle, Clare"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Understanding Self-Predictive Learning for Reinforcement Learning.

Please choose a person to relate this publication to

Christoper Lyle

John Lyle

Allan Lyle

Bernd Claren

Hildegard Clarenz-Löhnert

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Understanding Self-Predictive Learning for Reinforcement Learning.