Author

Kibaek Kim

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Preprint Sep 2026

Privacy Foundations for Multi-Institutional Scientific Artificial Intelligence

Scientific artificial intelligence (AI), spanning foundation models (FMs) to federated data-analysis pipelines, is becoming shared infrastructure across national laboratories, universities, hospitals, and industrial partners. This collaboration creates privacy risks whose natural unit is often an institution's particip...

O. Kotevska, Sumit Kumar Jha, A. Bellet et al. · 1 citation

#artificial intelligence Preprint Sep 2026

Compressed Active Subspaces for Scalable Bayesian Inference

This work proposes Compressed Active Subspaces (CAS), a scalable approach that first maps the model parameters to a compressed space using a structured isometric embedding and then constructs the active subspace within this reduced parameterization.

Thomas Flynn, Sanket R. Jantre, Byung-Jun Yoon et al. · 0 citations

#federated learning Preprint Sep 2026

Federated Learning on the American Science Cloud using APPFL

It is argued that offering federated computing as an important AmSC service would unlock privacy-constrained scientific collaborations, enabling public-private partnerships in model building while exercising and enhancing the platform's own federated infrastructure.

Zilinghan Li, Abhijith Chunduru, H. Krishnan et al. · 0 citations