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cs.LG2024
Scalify: scale propagation for efficient low-precision LLM training
Paul Balança, Sam Hosegood, Carlo Luschi +1
Low-precision formats such as float8 have been introduced in machine learning accelerated hardware to improve computational efficiency for large language models training and infere…
cs.LG2024
Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory
Alexander Mathiasen, Hatem Helal, Paul Balanca +6
Density Functional Theory (DFT) accurately predicts the quantum chemical properties of molecules, but scales as . Schütt et al. (2019) successfully appro…