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 • 30 Sep 2020 • Alexander Mathiasen, Frederik Hvilshøj
Orthogonal weight matrices are used in many areas of deep learning.
no code implementations • 29 Sep 2020 • Alexander Mathiasen, Frederik Hvilshøj
Using FID as an additional loss for Generative Adversarial Networks improves their FID.
1 code implementation • NeurIPS 2020 • Alexander Mathiasen, Frederik Hvilshøj, Jakob Rødsgaard Jørgensen, Anshul Nasery, Davide Mottin
We present an algorithm that is fast enough to speed up several matrix operations.
no code implementations • NeurIPS 2019 • Allan Grønlund, Lior Kamma, Kasper Green Larsen, Alexander Mathiasen, Jelani Nelson
To date, the strongest known generalization (upper bound) is the $k$th margin bound of Gao and Zhou (2013).
no code implementations • 30 Jan 2019 • Allan Grønlund, Kasper Green Larsen, Alexander Mathiasen
A common goal in a long line of research, is to maximize the smallest margin using as few base hypotheses as possible, culminating with the AdaBoostV algorithm by (R{\"a}tsch and Warmuth [JMLR'04]).
2 code implementations • 25 Jan 2017 • Allan Grønlund, Kasper Green Larsen, Alexander Mathiasen, Jesper Sindahl Nielsen, Stefan Schneider, Mingzhou Song
We present all the existing work that had been overlooked and compare the various solutions theoretically.