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20192026
most citedMonotone-Value Neural Networks: Exploiting Preference Monotonicity in Combinatorial Assignment

7 citations · 23 across the 14 of their papers we have counts for

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math.OC2026

Implicit Regularization of Large Neural Networks via Mean-Field Formulation

Beatrice Acciaio, Jakob Heiss, Gudmund Pammer +1

We propose a mathematical framework to explain implicit regularization from early stopping during the training of overparametrized neural networks. In the mean-field limit, the par…

stat.ML2026

JUCAL: Jointly Calibrating Aleatoric and Epistemic Uncertainty in Classification Tasks

Jakob Heiss, Sören Lambrecht, Jakob Weissteiner +4

We study post-calibration uncertainty for trained ensembles of classifiers. Specifically, we consider both aleatoric (label noise) and epistemic (model) uncertainty. Among the most…