Temporal Evaluation of Probability Calibration with Experimental Errors
Paper i proceeding, 2025

The quantification of uncertainties associated with neural network predictions can facilitate optimal decision-making and accelerate workflows where time and resource efficiency are essential.

Författare

Hannah Rosa Friesacher

AstraZeneca AB

KU Leuven

Emma Svensson

Johannes Kepler Universität Linz (JKU)

AstraZeneca AB

Ádám Arany

KU Leuven

Lewis H. Mervin

AstraZeneca AB

Ola Engkvist

Chalmers, Data- och informationsteknik, Data Science och AI

AstraZeneca AB

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 14894 LNCS 13-20
9783031723803 (ISBN)

1st International Workshop on AI in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024
Lugano, Switzerland,

Ämneskategorier

Bioinformatik (beräkningsbiologi)

DOI

10.1007/978-3-031-72381-0_2

Mer information

Senast uppdaterat

2024-10-11