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Seyed Kamyar Seyed Ghasemipour

Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters


May 27, 2022
Seyed Kamyar Seyed Ghasemipour, Shixiang Shane Gu, Ofir Nachum

* Our codebase can be found at https://github.com/google-research/google-research/tree/master/jrl 

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Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding


May 23, 2022
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi


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Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning


Apr 12, 2022
Seyed Kamyar Seyed Ghasemipour, Daniel Freeman, Byron David, Shixiang Shane Gu, Satoshi Kataoka, Igor Mordatch

* Accompanying project webpage can be found at: https://sites.google.com/view/learning-direct-assembly 

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Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning


Mar 15, 2022
Satoshi Kataoka, Seyed Kamyar Seyed Ghasemipour, Daniel Freeman, Igor Mordatch

* Our accompanying project webpage can be found at: https://sites.google.com/view/bimanual-attachment 

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Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization


Oct 10, 2021
Shixiang Shane Gu, Manfred Diaz, Daniel C. Freeman, Hiroki Furuta, Seyed Kamyar Seyed Ghasemipour, Anton Raichuk, Byron David, Erik Frey, Erwin Coumans, Olivier Bachem


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EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL


Jul 21, 2020
Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Shane Gu


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A Divergence Minimization Perspective on Imitation Learning Methods


Nov 06, 2019
Seyed Kamyar Seyed Ghasemipour, Richard Zemel, Shixiang Gu

* Published at Conference on Robot Learning (CoRL) 2019. For datasets and reproducing results please refer to https://github.com/KamyarGh/rl_swiss/blob/master/reproducing/fmax_paper.md 

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