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

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

3 December 2022

Riley J. Hickman

Aniket N. Zinzuwadia

Benjamín Sánchez-Lengeling

A. Aspuru‐Guzik

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

17 / 17 papers shown

Title
Self-focusing virtual screening with active design space pruning David E. Graff Matteo Aldeghi Joseph A. Morrone K. E. Jordan Edward O. Pyzer-Knapp Connor W. Coley 51 25 0 03 May 2022
Reliable Graph Neural Networks for Drug Discovery Under Distributional Shift Kehang Han Balaji Lakshminarayanan J. Liu OOD GNN 44 33 0 25 Nov 2021
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning Zachary Nado Neil Band Mark Collier Josip Djolonga Michael W. Dusenberry ... D. Sculley Balaji Lakshminarayanan Jasper Snoek Y. Gal Dustin Tran UQCV ELM 61 96 0 07 Jun 2021
Assigning Confidence to Molecular Property Prediction AkshatKumar Nigam R. Pollice Matthew F. D. Hurley Riley J. Hickman Matteo Aldeghi Naruki Yoshikawa Seyone Chithrananda Vincent A. Voelz Alán Aspuru-Guzik AI4CE 91 46 0 23 Feb 2021
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness Jeremiah Zhe Liu Zi Lin Shreyas Padhy Dustin Tran Tania Bedrax-Weiss Balaji Lakshminarayanan UQCV BDL 142 446 0 17 Jun 2020
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction Lior Hirschfeld Kyle Swanson Kevin Kaichuang Yang Regina Barzilay Connor W. Coley 66 191 0 20 May 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 76 108 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 58 94 0 02 Mar 2020
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 148 1,688 0 06 Jun 2019
Evidential Deep Learning to Quantify Classification Uncertainty Murat Sensoy Lance M. Kaplan M. Kandemir OOD UQCV EDL BDL 146 986 0 05 Jun 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 558 3,109 0 04 Jun 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 148 9,383 0 09 Feb 2018
A Network Perspective on Stratification of Multi-Label Data Piotr Szymañski Tomasz Kajdanowicz 38 85 0 27 Apr 2017
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 315 1,822 0 02 Mar 2017
GPflow: A Gaussian process library using TensorFlow A. G. Matthews Mark van der Wilk T. Nickson Keisuke Fujii A. Boukouvalas Pablo León-Villagrá Zoubin Ghahramani J. Hensman GP 67 664 0 27 Oct 2016
Deep Kernel Learning A. Wilson Zhiting Hu Ruslan Salakhutdinov Eric Xing BDL 212 885 0 06 Nov 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 191 1,511 0 08 Jun 2015

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