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SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular
  Conformers

SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers

15 February 2023
Michael R. Maser
Ji Won Park
J. Lin
Jae Hyeon Lee
Nathan C. Frey
Andrew Watkins
ArXivPDFHTML

Papers citing "SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers"

5 / 5 papers shown
Title
MoleCLUEs: Molecular Conformers Maximally In-Distribution for Predictive
  Models
MoleCLUEs: Molecular Conformers Maximally In-Distribution for Predictive Models
Michael R. Maser
Natasa Tagasovska
Jae Hyeon Lee
Andrew Watkins
31
0
0
20 Jun 2023
Understanding Collapse in Non-Contrastive Siamese Representation
  Learning
Understanding Collapse in Non-Contrastive Siamese Representation Learning
Alexander C. Li
Alexei A. Efros
Deepak Pathak
SSL
40
33
0
29 Sep 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic
  Graphs
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs
Yi-Lun Liao
Tess E. Smidt
75
211
0
23 Jun 2022
Contrastive Representation Learning: A Framework and Review
Contrastive Representation Learning: A Framework and Review
Phúc H. Lê Khắc
Graham Healy
A. Smeaton
SSL
AI4TS
164
678
0
10 Oct 2020
MoleculeNet: A Benchmark for Molecular Machine Learning
MoleculeNet: A Benchmark for Molecular Machine Learning
Zhenqin Wu
Bharath Ramsundar
Evan N. Feinberg
Joseph Gomes
C. Geniesse
Aneesh S. Pappu
K. Leswing
Vijay S. Pande
OOD
162
1,766
0
02 Mar 2017
1