3 papers
cs.LG2025
When three experiments are better than two: Avoiding intractable correlated aleatoric uncertainty by leveraging a novel bias--variance tradeoff
Paul Scherer, Andreas Kirsch, Jake P. Taylor-King
Real-world experimental scenarios are characterized by the presence of heteroskedastic aleatoric uncertainty, and this uncertainty can be correlated in batched settings. The bias--…
cs.LG2025
No Foundations without Foundations -- Why semi-mechanistic models are essential for regulatory biology
Luka KovaÄeviÄ, Thomas Gaudelet, James Opzoomer +5
Despite substantial efforts, deep learning has not yet delivered a transformative impact on elucidating regulatory biology, particularly in the realm of predicting gene expression…
cs.LG2024
PyRelationAL: a python library for active learning research and development
Paul Scherer, Alison Pouplin, Alice Del Vecchio +6
Active learning (AL) is a sub-field of ML focused on the development of methods to iteratively and economically acquire data by strategically querying new data points that are the…