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Achieving Well-Informed Decision-Making in Drug Discovery: A
  Comprehensive Calibration Study using Neural Network-Based Structure-Activity
  Models

Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models

19 July 2024
Hannah Rosa Friesacher
O. Engkvist
Lewis H. Mervin
Yves Moreau
Adam Arany
ArXivPDFHTML

Papers citing "Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models"

2 / 2 papers shown
Title
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
270
5,660
0
05 Dec 2016
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
279
9,136
0
06 Jun 2015
1