3 papers
stat.ML2026
Learning to Emulate Chaos: Adversarial Optimal Transport Regularization
Gabriel Melo, Leonardo Santiago, Peter Y. Lu
Chaos arises in many complex dynamical systems, from weather to power grids, but is difficult to accurately model with data-driven methods such as machine learning emulators. While…
cs.LG2025
Hierarchical Implicit Neural Emulators
Ruoxi Jiang, Xiao Zhang, Karan Jakhar +4
Neural PDE solvers offer a powerful tool for modeling complex dynamical systems, but often struggle with error accumulation over long time horizons and maintaining stability and ph…
cs.LG2024
Embed and Emulate: Contrastive representations for simulation-based inference
Ruoxi Jiang, Peter Y. Lu, Rebecca Willett
Scientific modeling and engineering applications rely heavily on parameter estimation methods to fit physical models and calibrate numerical simulations using real-world measuremen…