AdsorbRL: Deep Multi-Objective Reinforcement Learning for Inverse Catalysts Design

4 December 2023

Papers citing "AdsorbRL: Deep Multi-Objective Reinforcement Learning for Inverse Catalysts Design"

9 / 9 papers shown

Title
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts Richard Tran Janice Lan Muhammed Shuaibi Brandon M. Wood Siddharth Goyal ... Jehad Abed Oleksandr Voznyy Edward H. Sargent Zachary W. Ulissi C. L. Zitnick 107 181 0 17 Jun 2022
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 301 533 0 20 Oct 2020
An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage C. L. Zitnick L. Chanussot Abhishek Das Siddharth Goyal Javier Heras-Domingo ... Kevin Tran Brandon M. Wood Junwoong Yoon Devi Parikh Zachary W. Ulissi 66 75 0 14 Oct 2020
Conservative Q-Learning for Offline Reinforcement Learning Aviral Kumar Aurick Zhou George Tucker Sergey Levine OffRL OnRL 146 1,836 0 08 Jun 2020
Behavior Regularized Offline Reinforcement Learning Yifan Wu George Tucker Ofir Nachum OffRL 97 690 0 26 Nov 2019
Optimization of Molecules via Deep Reinforcement Learning Zhenpeng Zhou S. Kearnes Li Li R. Zare Patrick F. Riley AI4CE 115 543 0 19 Oct 2018
A Brief Survey of Deep Reinforcement Learning Kai Arulkumaran M. Deisenroth Miles Brundage Anil Anthony Bharath OffRL 133 2,830 0 19 Aug 2017
Hindsight Experience Replay Marcin Andrychowicz Dwight Crow Alex Ray Jonas Schneider Rachel Fong Peter Welinder Bob McGrew Joshua Tobin Pieter Abbeel Wojciech Zaremba OffRL 280 2,339 0 05 Jul 2017
Prioritized Experience Replay Tom Schaul John Quan Ioannis Antonoglou David Silver OffRL 231 3,796 0 18 Nov 2015