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Accurate, reliable and interpretable solubility prediction of druglike
  molecules with attention pooling and Bayesian learning

Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning

29 September 2022
Seongok Ryu
Sumin Lee
ArXivPDFHTML

Papers citing "Accurate, reliable and interpretable solubility prediction of druglike molecules with attention pooling and Bayesian learning"

5 / 5 papers shown
Title
Understanding active learning of molecular docking and its applications
Understanding active learning of molecular docking and its applications
Jeonghyeon Kim
Juno Nam
Seongok Ryu
35
0
0
14 Jun 2024
Bidirectional Generation of Structure and Properties Through a Single
  Molecular Foundation Model
Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Model
Jinho Chang
Jong Chul Ye
AI4CE
22
29
0
19 Nov 2022
Accelerating high-throughput virtual screening through molecular
  pool-based active learning
Accelerating high-throughput virtual screening through molecular pool-based active learning
David E. Graff
E. Shakhnovich
Connor W. Coley
87
142
0
13 Dec 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
181
1,778
0
02 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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