no code implementations • 6 Feb 2024 • Alexander Mathiasen, Hatem Helal, Paul Balanca, Adam Krzywaniak, Ali Parviz, Frederik Hvilshøj, Blazej Banaszewski, Carlo Luschi, Andrew William Fitzgibbon
For comparison, Sch\"utt et al. (2019) spent 626 hours creating a dataset on which they trained their NN for 160h, for a total of 786h; our method achieves comparable performance within 31h.
2 code implementations • NeurIPS 2023 • Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew Fitzgibbon, Dominic Masters
Similar benefits are yet to be unlocked for quantum chemistry, where the potential of deep learning is constrained by comparatively small datasets with 100k to 20M training examples.
no code implementations • 29 Sep 2023 • Sergio P. Perez, Yan Zhang, James Briggs, Charlie Blake, Josh Levy-Kramer, Paul Balanca, Carlo Luschi, Stephen Barlow, Andrew William Fitzgibbon
FP8 formats are gaining popularity to boost the computational efficiency for training and inference of large deep learning models.