Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS

3 December 2022

Papers citing "Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS"

7 / 7 papers shown

Title
Improving Self-supervised Molecular Representation Learning using Persistent Homology Yuankai Luo Lei Shi Veronika Thost SSL 17 8 0 29 Nov 2023
Accelerating high-throughput virtual screening through molecular pool-based active learning David E. Graff E. Shakhnovich Connor W. Coley 76 139 0 13 Dec 2020
Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge Florian Hase Matteo Aldeghi Riley J. Hickman L. Roch Alán Aspuru-Guzik 43 103 0 26 Mar 2020
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 35 94 0 02 Mar 2020
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 157 1,748 0 02 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015