2 papers
cs.LG2026
Deep Wave Network for Modeling Multi-Scale Physical Dynamics
Alexander I. Khrabry, Edward A. Startsev, Andrew T. Powis +1
Performance of deep learning models is strongly governed by architectural capacity, with width and depth as primary controls. However, in physical-science applications, models are…
cs.AI2025
Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems
Alexander Khrabry, Edward Startsev, Andrew Powis +1
We propose a novel efficient architecture for learning long-term evolution in complex multi-scale physical systems which is based on the idea of separation of scales. Structures of…