2 papers
cs.LG2026
Stein Kernelized Molecular Dynamics for Active Learning of Interatomic Potentials
Joanna Zou, Fraser Birks, Dallas Foster +1
Machine learning interatomic potentials (MLIPs) enable efficient and accurate atomistic simulations but depend critically on the quality and diversity of the training data. We intr…
cs.LG2025
MoWE : A Mixture of Weather Experts
Dibyajyoti Chakraborty, Romit Maulik, Peter Harrington +3
Data-driven weather models have recently achieved state-of-the-art performance, yet progress has plateaued in recent years. This paper introduces a Mixture of Experts (MoWE) approa…