most citedPhysics-Informed Surrogates for Temperature Prediction of Multi-Tracks in Laser Powder Bed Fusion

2 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Uncertainty quantification in model discovery by distilling interpretable material constitutive models from Gaussian process posteriors

David Anton, Henning Wessels, Ulrich Römer +2

Constitutive model discovery refers to the task of identifying an appropriate model structure, usually from a predefined model library, while simultaneously inferring its material…

cs.CE2025

Unsupervised Constitutive Model Discovery from Sparse and Noisy Data

Vahab Knauf Narouie, Jorge-Humberto Urrea-Quintero, Fehmi Cirak +1

Recently, unsupervised constitutive model discovery has gained attention through frameworks based on the Virtual Fields Method (VFM), most prominently the EUCLID approach. However,…

cs.LG2025

Automated Constitutive Model Discovery by Pairing Sparse Regression Algorithms with Model Selection Criteria

Jorge-Humberto Urrea-Quintero, David Anton, Laura De Lorenzis +1

The automated discovery of constitutive models from data has recently emerged as a promising alternative to the traditional model calibration paradigm. In this work, we present a f…

cs.CE20252 cited

Physics-Informed Surrogates for Temperature Prediction of Multi-Tracks in Laser Powder Bed Fusion

Hesameddin Safari, Henning Wessels

Modeling plays a critical role in additive manufacturing (AM), enabling a deeper understanding of underlying processes. Parametric solutions for such models are of great importance…

cs.CE20241 cited

Model-based reinforcement corrosion prediction: Continuous calibration with Bayesian optimization and corrosion wire sensor data

A. Potnis, M. Macier, T. Leusmann +3

Chloride-induced corrosion significantly contributes to the degradation of reinforced concrete structures, making accurate predictions of chloride migration and its effects on mate…