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Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve


Dec 07, 2022
Juhan Bae, Michael R. Zhang, Michael Ruan, Eric Wang, So Hasegawa, Jimmy Ba, Roger Grosse

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* 22 pages, 9 figures 

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Learning Domain Invariant Representations in Goal-conditioned Block MDPs


Oct 28, 2021
Beining Han, Chongyi Zheng, Harris Chan, Keiran Paster, Michael R. Zhang, Jimmy Ba

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* NeurIPS2021 
* 33 pages 

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Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization


Apr 28, 2021
Michael R. Zhang, Tom Le Paine, Ofir Nachum, Cosmin Paduraru, George Tucker, Ziyu Wang, Mohammad Norouzi

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* ICLR 2021. 17 pages 

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Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes


Apr 23, 2021
James Lucas, Juhan Bae, Michael R. Zhang, Stanislav Fort, Richard Zemel, Roger Grosse

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* 15 pages in main paper, 4 pages of references, 24 pages in appendix. 29 figures in total 

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Benchmarks for Deep Off-Policy Evaluation


Mar 30, 2021
Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine

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* ICLR 2021 paper. Policies and evaluation code are available at https://github.com/google-research/deep_ope 

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Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes


Jan 27, 2020
Silviu Pitis, Michael R. Zhang

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* 10 pages, 3 figures. To appear in proceedings of AAMAS 2020 

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Lookahead Optimizer: k steps forward, 1 step back


Jul 19, 2019
Michael R. Zhang, James Lucas, Geoffrey Hinton, Jimmy Ba

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* 8 pages 

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