85 citations · 134 across the 12 of their papers we have counts for
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cs.DC2026
A Portable and Versatile Limited-Memory BFGS Implementation in PETSc/TAO
Hansol Suh, Tobin Isaac, Alp Dener +3
The limited-memory BFGS (L-BFGS) Hessian update scheme is the critical kernel in many quasi-Newton optimization algorithms. The most common approach to implementing L-BFGS uses $2m…
cs.LG2026
Scalable Cross-Facility Federated Learning for Scientific Foundation Models on Multiple Supercomputers
Yijiang Li, Zilinghan Li, Kyle Chard +4
Artificial Intelligence for scientific applications increasingly requires training large models on data that cannot be centralized due to privacy constraints, data sovereignty, or…