2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Black-Box Uncertainty Estimation for Deep Learning Models in Atomistic Simulations
Idan Fonea, Amir Peles, Sivan Niv +2
We analyze an ensemble-based approach for uncertainty quantification (UQ) in atomistic neural networks. This method generates an epistemic uncertainty signal without requiring chan…
Reduced Order Modeling of Partial Differential Equations on Parameter-Dependent Domains Using Deep Neural Networks
Martina BukaÄ, Iva ManojloviÄ, Boris Muha +1
Partial differential equations (PDEs) are widely used for modeling various physical phenomena. These equations often depend on certain parameters, necessitating either the identifi…
Fractal analysis of slow-fast and regular systems: A survey of recent results and future perspectives
Renato Huzak, Goran RadunoviÄ, Vesna ŽupanoviÄ
We survey recent developments in fractal analysis of regular and slow-fast dynamical systems using Minkowski dimension. Our focus is on spiral trajectories near monodromic limit pe…
Rethinking Broken Object Level Authorization Attacks Under Zero Trust Principle
Anbin Wu, Zhiyong Feng, Ruitao Feng +2
RESTful APIs facilitate data exchange between applications, but they also expose sensitive resources to potential exploitation. Broken Object Level Authorization (BOLA) is the top…