Reducing the Cost of Quantum Chemical Data By Backpropagating Through
Density Functional Theory

Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory

6 February 2024

Alexander Mathiasen

Paul Balanca

Adam Krzywaniak

Frederik Hvilshoj

Bla.zej Banaszewski

Carlo Luschi

Andrew William Fitzgibbon

Papers citing "Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory"

3 / 3 papers shown

Title
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 195 1,232 0 08 Jan 2021
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 221 500 0 20 Oct 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,453 0 23 Jan 2020