1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
Structure-Preserving Neural Surrogates with Tractable Uncertainty Quantification
Handi Zhang, Adrienne M. Propp, Brooks Kinch +2
Recent advances in scientific machine learning provide a means of near-real-time solution to partial differential equations (PDEs), but lack the theoretical underpinnings of conven…
cs.LG2024★ 1 cited
Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity
Handi Zhang, Langchen Liu, Lu Lu
By leveraging neural networks, the emerging field of scientific machine learning (SciML) offers novel approaches to address complex problems governed by partial differential equati…