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cs.LG2026
Do Physics Foundation Models Learn Generalizable Physics? A Bias-Aware Benchmark Across Physical Regimes and Distribution Shifts
Mengdi Chu, Yang Liu, Ayan Biswas +1
Recent physics foundation models claim general spatiotemporal forecasting ability, yet their evaluations often collapse performance into a single average score under a fixed traini…
cs.LG2026
PDE foundation model-accelerated inverse estimation of system parameters in inertial confinement fusion
Mahindra Rautela, Alexander Scheinker, Bradley Love +4
PDE foundation models are typically pretrained on large, diverse corpora of PDE datasets and can be adapted to new settings with limited task-specific data. However, most downstrea…
cs.LG2025
A Partitioned Sparse Variational Gaussian Process for Fast, Distributed Spatial Modeling
Michael Grosskopf, Kellin Rumsey, Ayan Biswas +1
The next generation of Department of Energy supercomputers will be capable of exascale computation. For these machines, far more computation will be possible than that which can be…