Rick Archibald

most citedMGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

35 citations · 39 across the 7 of their papers we have counts for

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cs.LG2025

Federated Learning on Stochastic Neural Networks

Jingqiao Tang, Ryan Bausback, Feng Bao +1

Federated learning is a machine learning paradigm that leverages edge computing on client devices to optimize models while maintaining user privacy by ensuring that local data rema…

cs.LG2024

Sparse $L^{1}$ -Autoencoders for Scientific Data Compression

Matthias Chung, Rick Archibald, Paul Atzberger +1

Scientific datasets present unique challenges for machine learning-driven compression methods, including more stringent requirements on accuracy and mitigation of potential invalid…

Federated Learning on Stochastic Neural Networks

Sparse L1-Autoencoders for Scientific Data Compression

Sparse $L^{1}$ -Autoencoders for Scientific Data Compression