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cs.LG2024★ 1 cited
Feasibility Study on Active Learning of Smart Surrogates for Scientific Simulations
Pradeep Bajracharya, Javier Quetzalcóatl Toledo-Marín, Geoffrey Fox +2
High-performance scientific simulations, important for comprehension of complex systems, encounter computational challenges especially when exploring extensive parameter spaces. Th…
cs.LG2024
Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework
Yubo Ye, Sumeet Vadhavkar, Xiajun Jiang +3
Modern applications increasingly require unsupervised learning of latent dynamics from high-dimensional time-series. This presents a significant challenge of identifiability: many…