| Combating mode collapse in GAN training: An empirical analysis using hessian eigenvalues R Durall, A Chatzimichailidis, P Labus, J Keuper arXiv preprint arXiv:2012.09673, 2020 | 22 | 2020 |
| Proxsgd: Training structured neural networks under regularization and constraints Y Yang, Y Yuan, A Chatzimichailidis, RJG van Sloun, L Lei, S Chatzinotas International Conference on Learning Representations (ICLR) 2020, 2020 | 18 | 2020 |
| Gradvis: Visualization and second order analysis of optimization surfaces during the training of deep neural networks A Chatzimichailidis, J Keuper, FJ Pfreundt, NR Gauger 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing …, 2019 | 2 | 2019 |
| MSM: Multi-stage Multicuts for Scalable Image Clustering K Ho, A Chatzimichailidis, M Keuper, J Keuper High Performance Computing: ISC High Performance Digital 2021 International …, 2021 | 1 | 2021 |
| GSparsity: Unifying Network Pruning and Neural Architecture Search by Group Sparsity A Chatzimichailidis, A Zela, J Keuper, Y Yang | | 2022 |
| Group Sparsity: A Unified Framework for Network Pruning and Neural Architecture Search A Chatzimichailidis, SS Arber Zela, P Labus, J Keuper, F Hutter, Y Yang CVPR NAS Workshop, 2021 | | 2021 |
| Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues R Durall Lopez, A Chatzimichailidis, P Labus, J Keuper | | 2020 |
| MLHPC 2019 G Heinrich, I Frosio, S Prudhomme, S Adrian, GE Moon, D Newman-Griffis, ... | | |
| Studies on time dependent activity distributions for the SAFIR project A Chatzimichailidis | | |
