Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks

13 July 2021

Jonas Busk

Peter Bjørn Jørgensen

Papers citing "Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks"

20 / 20 papers shown

Title
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification Jonas Teufel Annika Leinweber Pascal Friederich 46 0 0 03 Apr 2025
Advancements in Molecular Property Prediction: A Survey of Single and Multimodal Approaches Tanya Liyaqat T. Ahmad Chandni Saxena 32 2 0 18 Aug 2024
Validation of ML-UQ calibration statistics using simulated reference values: a sensitivity analysis Pascal Pernot 19 0 0 01 Mar 2024
Negative impact of heavy-tailed uncertainty and error distributions on the reliability of calibration statistics for machine learning regression tasks Pascal Pernot 33 1 0 15 Feb 2024
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force Fields Joshua A. Vita Amit Samanta Fei Zhou Vincenzo Lordi 25 2 0 01 Feb 2024
AIRI: Predicting Retention Indices and their Uncertainties using Artificial Intelligence Lewis Y. Geer Stephen E. Stein W. G. Mallard D. Slotta 17 7 0 03 Jan 2024
Coherent energy and force uncertainty in deep learning force fields Peter Bjørn Jørgensen Jonas Busk Ole Winther Mikkel N. Schmidt 13 3 0 07 Dec 2023
Can bin-wise scaling improve consistency and adaptivity of prediction uncertainty for machine learning regression ? Pascal Pernot 23 2 0 18 Oct 2023
Band-gap regression with architecture-optimized message-passing neural networks Tim Bechtel Daniel T. Speckhard Jonathan Godwin Claudia Ambrosch-Draxl 24 0 0 12 Sep 2023
Calibration in Machine Learning Uncertainty Quantification: beyond consistency to target adaptivity Pascal Pernot 25 9 0 12 Sep 2023
Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture Search Shengli Jiang Shiyi Qin Reid C. Van Lehn Prasanna Balaprakash Victor M. Zavala AI4CE 29 7 0 19 Jul 2023
MUBen: Benchmarking the Uncertainty of Molecular Representation Models Yinghao Li Lingkai Kong Yuanqi Du Yue Yu Yuchen Zhuang Wenhao Mu Chao Zhang 29 9 0 14 Jun 2023
Stratification of uncertainties recalibrated by isotonic regression and its impact on calibration error statistics P. Pernot 14 4 0 08 Jun 2023
Properties of the ENCE and other MAD-based calibration metrics P. Pernot 11 5 0 17 May 2023
Validation of uncertainty quantification metrics: a primer based on the consistency and adaptivity concepts P. Pernot 11 6 0 13 Mar 2023
On the role of Model Uncertainties in Bayesian Optimization Jonathan Foldager Mikkel Jordahn Lars Kai Hansen Michael Riis Andersen 19 4 0 14 Jan 2023
Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS Gary Tom Riley J. Hickman Aniket N. Zinzuwadia A. Mohajeri Benjamín Sánchez-Lengeling A. Aspuru‐Guzik 21 16 0 03 Dec 2022
MaterialsAtlas.org: A Materials Informatics Web App Platform for Materials Discovery and Survey of State-of-the-Art Jianjun Hu Stanislav Stefanov Yuqi Song Sadman Sadeed Omee Steph-Yves M. Louis Edirisuriya M Dilanga Siriwardane Yong Zhao 11 33 0 09 Sep 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015