2 papers
cs.RO2026
LeWAM: End-to-End World and Action Modeling with JEPAs
Minghao Fu, Tavis Siebert, Eryk Halicki +1
Joint-embedding predictive architectures (JEPAs) learn compact latent world models without pixel reconstruction. Existing JEPA pipelines typically train visual representations and…
cs.LG2024
Time Series Viewmakers for Robust Disruption Prediction
Dhruva Chayapathy, Tavis Siebert, Lucas Spangher +3
Machine Learning guided data augmentation may support the development of technologies in the physical sciences, such as nuclear fusion tokamaks. Here we endeavor to study the probl…