3 papers
stat.ML2026
Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later
Arnaud Vadeboncoeur, Gregory Duthé, Mark Girolami +1
Uncertainty Quantification (UQ) is paramount for inference in engineering. A common inference task is to recover full-field information of physical systems from a small number of n…
cs.LG2026
PiGGO: Physics-Guided Learnable Graph Kalman Filters for Virtual Sensing of Nonlinear Dynamic Structures under Uncertainty
Marcus Haywood-Alexander, Gregory Duthé, Eleni Chatzi
Digital twins provide a powerful paradigm for diagnostic and prognostic tasks in the monitoring and control of engineered systems; however, their deployment for complex structures…
cs.LG2025
A Mechanistic Analysis of Transformers for Dynamical Systems
Gregory Duthé, Gregory Duthé, Nikolaos Evangelou +3
Transformers are increasingly adopted for modeling and forecasting time-series, yet their internal mechanisms remain poorly understood from a dynamical systems perspective. In cont…