ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

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ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

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Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Model uncertainties in action effects and load bearing capacity calculation in statically indeterminate reinforced concrete structures

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

A FEM modelling workflow to simulate THM effects in the rock around nuclear waste packages

Predicting the long-term collective behaviour of fish pairs with deep learning

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Graph generative deep learning models with an application to circuit topologies

Understanding generalization and robustness in modern deep learning

Influence of model uncertainty and long term deformations in action effects calculation in reinforced concrete structures

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Gibbs sampling the posterior of neural networks

Luminosity determination using Z boson production at the CMS experiment

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Random matrix methods for high-dimensional machine learning models