Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science

15 October 2021

Papers citing "Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science"

6 / 6 papers shown

Title
Invariant multiscale neural networks for data-scarce scientific applications I. Schurov D. Alforov M. Katsnelson A. Bagrov A. Itin AI4CE 34 0 0 12 Jun 2024
On the Importance of Calibration in Semi-supervised Learning Charlotte Loh Rumen Dangovski Shivchander Sudalairaj Seung-Jun Han Ligong Han Leonid Karlinsky Marin Soljacic Akash Srivastava 27 6 0 10 Oct 2022
Equivariant Contrastive Learning Rumen Dangovski Li Jing Charlotte Loh Seung-Jun Han Akash Srivastava Brian Cheung Pulkit Agrawal Marin Soljacic 31 77 0 28 Oct 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 171 246 0 01 May 2021
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure Samuel Kim Peter Y. Lu Charlotte Loh Jamie Smith Jasper Snoek M. Soljavcić BDL AI4CE 74 17 0 23 Apr 2021
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 203 1,240 0 08 Jan 2021