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Analysis of Atom-level pretraining with Quantum Mechanics (QM) data for
  Graph Neural Networks Molecular property models

Analysis of Atom-level pretraining with Quantum Mechanics (QM) data for Graph Neural Networks Molecular property models

23 May 2024
Jose A. Arjona-Medina
Ramil I. Nugmanov
    AI4CE
ArXivPDFHTML

Papers citing "Analysis of Atom-level pretraining with Quantum Mechanics (QM) data for Graph Neural Networks Molecular property models"

4 / 4 papers shown
Title
Context-enriched molecule representations improve few-shot drug
  discovery
Context-enriched molecule representations improve few-shot drug discovery
Johannes Schimunek
Philipp Seidl
Lukas Friedrich
Daniel Kuhn
F. Rippmann
Sepp Hochreiter
G. Klambauer
42
26
0
24 Apr 2023
A Systematic Survey of Chemical Pre-trained Models
A Systematic Survey of Chemical Pre-trained Models
Jun-Xiong Xia
Yanqiao Zhu
Yuanqi Du
Stan Z.Li
AI4CE
49
50
0
29 Oct 2022
Train Short, Test Long: Attention with Linear Biases Enables Input
  Length Extrapolation
Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
Ofir Press
Noah A. Smith
M. Lewis
234
690
0
27 Aug 2021
Contrastive Representation Learning: A Framework and Review
Contrastive Representation Learning: A Framework and Review
Phúc H. Lê Khắc
Graham Healy
A. Smeaton
SSL
AI4TS
146
670
0
10 Oct 2020
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