| Fast Exact k-Means, k-Medians and Bregman Divergence Clustering in 1d A Grønlund, KG Larsen, A Mathiasen, JS Nielsen, S Schneider, M Song arXiv preprint arXiv:1701.07204, 2017 | 65 | 2017 |
| Backpropagating through Fr\'echet Inception Distance A Mathiasen, F Hvilshøj arXiv preprint arXiv:2009.14075, 2020 | 23 | 2020 |
| Margin-Based Generalization Lower Bounds for Boosted Classifiers A Grønlund, L Kamma, KG Larsen, A Mathiasen, J Nelson Advances in Neural Information Processing Systems, 11963-11972, 2019 | 16 | 2019 |
| Fast Fréchet Inception Distance A Mathiasen, F Hvilshøj https://arxiv.org/abs/2009.14075, 2020 | 15 | 2020 |
| What if Neural Networks had SVDs? A Mathiasen, F Hvilshøj, JR Jørgsen, A Nasery, D Mottin https://arxiv.org/abs/2009.13977, 0 | 8* | |
| Optimal Minimal Margin Maximization with Boosting A Mathiasen, KG Larsen, A Grønlund International Conference on Machine Learning, 4392-4401, 2019 | 6 | 2019 |
| Generating QM1B with PySCF A Mathiasen, H Helal, K Klaser, P Balanca, J Dean, C Luschi, D Beaini, ... Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
| One Reflection Suffice A Mathiasen, F Hvilshøj https://arxiv.org/abs/2009.14554, 0 | 2* | |
| Reducing the Cost of Quantum Chemical Data By Backpropagating Through Density Functional Theory A Mathiasen, H Helal, P Balanca, A Krzywaniak, A Parviz, F Hvilshøj, ... arXiv preprint arXiv:2402.04030, 2024 | 1 | 2024 |
| Repurposing density functional theory to suit deep learning A Mathiasen, H Helal, P Balanca, K Klaeser, J Dean, C Luschi, D Beaini, ... 1st Workshop on the Synergy of Scientific and Machine Learning Modeling …, 2023 | 1 | 2023 |
| Faster Orthogonal Parameterization with Householder Matrices A Mathiasen, F Hvilshøj, JR Jørgensen, A Nasery, D Mottin ICML Workshop on Invertible Neural Networks and Normalizing Flows, 2020 | 1 | 2020 |
| Algorithmic Improvements to Boosting and Neural Networks A Mathiasen Aarhus Universitet, 2022 | | 2022 |
Allan GrønlundUniversity of AarhusVerified email at cs.au.dk
