3 papers
cs.LG2026
Beyond Compression: Training Latent Representations for Stable Long-Horizon Rollout in Neural Surrogate Solvers
Andreas E. Robertson, Ashley T. Lenau, John D. Shimanek +5
Latent neural surrogate solvers, or latent dynamics models, accelerate simulations of time-dependent physical systems by evolving a compressed latent space rather than resolving fu…
cs.LG2025
Microstructure-based Variational Neural Networks for Robust Uncertainty Quantification in Materials Digital Twins
Andreas E. Robertson, Samuel B. Inman, Ashley T. Lenau +4
Aleatoric uncertainties - irremovable variability in microstructure morphology, constituent behavior, and processing conditions - pose a major challenge to developing uncertainty-r…
cond-mat.mtrl-sci2022
Inferring topological transitions in pattern-forming processes with self-supervised learning
Marcin Abram, Keith Burghardt, Greg Ver Steeg +2
The identification and classification of transitions in topological and microstructural regimes in pattern-forming processes are critical for understanding and fabricating microstr…