1 citations · 1 across the 3 of their papers we have counts for
3 papers
Structurally Separated Uncertainty in Supervised Latent Variable Models
Tanmoy Mukherjee, Marius Kloft, Pierre Marquis +1
Predictive uncertainty is commonly decomposed into epistemic and aleatoric components, but standard decompositions often produce strongly correlated estimates because both quantiti…
Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov-Arnold Networks
Puyu Wang, Junyu Zhou, Philipp Liznerski +1
Kolmogorov--Arnold Networks (KANs) have recently emerged as a structured alternative to standard MLPs, yet a principled theory for their training dynamics, generalization, and priv…
Interpretable Tensor Fusion
Saurabh Varshneya, Antoine Ledent, Philipp Liznerski +4
Conventional machine learning methods are predominantly designed to predict outcomes based on a single data type. However, practical applications may encompass data of diverse type…