Seyed Kamyar Seyed Ghasemipour

According to our database, Seyed Kamyar Seyed Ghasemipour authored at least 15 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

ALOHA Unleashed: A Simple Recipe for Robot Dexterity.

Tony Z. Zhao, Jonathan Tompson, Danny Driess, Pete Florence, Kamyar Ghasemipour, Chelsea Finn, Ayzaan Wahid

CoRR, 2024

Learning Interactive Real-World Simulators.

Sherry Yang, Yilun Du, Seyed Kamyar Seyed Ghasemipour, Jonathan Tompson, Leslie Pack Kaelbling, Dale Schuurmans, Pieter Abbeel

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Learning Interactive Real-World Simulators.

Mengjiao Yang, Yilun Du, Kamyar Ghasemipour, Jonathan Tompson, Dale Schuurmans, Pieter Abbeel

CoRR, 2023

Bi-Manual Block Assembly via Sim-to-Real Reinforcement Learning.

Satoshi Kataoka, Youngseog Chung, Seyed Kamyar Seyed Ghasemipour, Pannag Sanketi, Shixiang Shane Gu, Igor Mordatch

CoRR, 2023

2022

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

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

CoRR, 2022

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

Satoshi Kataoka, Seyed Kamyar Seyed Ghasemipour, C. Daniel Freeman, Igor Mordatch

CoRR, 2022

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

Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L. Denton, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, Mohammad Norouzi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Seyed Kamyar Seyed Ghasemipour, Shixiang Shane Gu, Ofir Nachum

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

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

Proceedings of the International Conference on Machine Learning, 2022

2021

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

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

CoRR, 2021

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

Seyed Kamyar Seyed Ghasemipour, Dale Schuurmans, Shixiang Shane Gu

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies.

Seyed Kamyar Seyed Ghasemipour, Shixiang Gu, Richard S. Zemel

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Understanding the Relation Between Maximum-Entropy Inverse Reinforcement Learning and Behaviour Cloning.

Seyed Kamyar Seyed Ghasemipour, Shane Gu, Richard S. Zemel

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

A Divergence Minimization Perspective on Imitation Learning Methods.

Seyed Kamyar Seyed Ghasemipour, Richard S. Zemel, Shixiang Gu

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

Gradient-based Optimization of Neural Network Architecture.

Will Grathwohl, Elliot Creager, Seyed Kamyar Seyed Ghasemipour, Richard S. Zemel

Proceedings of the 6th International Conference on Learning Representations, 2018