BidhanChandra/UQ-ML-Calib: UQ-ML-Calib

Enhancing Uncertainty Quantification in Molecular Machine Learning This repository contains code and data for the paper: "Enhancing Uncertainty Quantification in Molecular Machine Learning: A Comparative Study of Deep Evidential Regression and Ensembles, with Post-Hoc Calibration."

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-10
DOI
https://doi.org/10.5281/zenodo.14998298
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00
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BidhanChandra/UQ-ML-Calib: UQ-ML-Calib

Zenodo (CERN European Organization for Nuclear Research)
Computational Drug Discovery Methods
article

BidhanChandra/UQ-ML-Calib: UQ-ML-Calib

article en

Abstract

Enhancing Uncertainty Quantification in Molecular Machine Learning This repository contains code and data for the paper: "Enhancing Uncertainty Quantification in Molecular Machine Learning: A Comparative Study of Deep Evidential Regression and Ensembles, with Post-Hoc Calibration."

Zenodo (CERN European Organization for Nuclear Research)
Aix-Marseille Université (FR)
Openalex Percentile: Top 56%
Computational Drug Discovery Methods
DOIOpen Access PDFOpenAlex
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BidhanChandra/UQ-ML-Calib: UQ-ML-Calib · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS