26 citations · 31 across the 4 of their papers we have counts for
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cs.DC2025
Optimizing Data Distribution and Kernel Performance for Efficient Training of Chemistry Foundation Models: A Case Study with MACE
Jesun Firoz, Franco Pellegrini, Mario Geiger +17
Chemistry Foundation Models (CFMs) that leverage Graph Neural Networks (GNNs) operating on 3D molecular graph structures are becoming indispensable tools for computational chemists…
cs.DC2024★ 5 cited
What Operations can be Performed Directly on Compressed Arrays, and with What Error?
Tripti Agarwal, Harvey Dam, Dorra Ben Khalifa +3
In response to the rapidly escalating costs of computing with large matrices and tensors caused by data movement, several lossy compression methods have been developed to significa…