| Learning DAGs from data with few root causes P Misiakos, C Wendler, M Püschel Advances in Neural Information Processing Systems 36, 16865-16888, 2023 | 10 | 2023 |
| Neural network approximation based on hausdorff distance of tropical zonotopes P Misiakos, G Smyrnis, G Retsinas, P Maragos International Conference on Learning Representations, 2022 | 9 | 2022 |
| The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data M Chevalley, J Sackett-Sanders, Y Roohani, P Notin, A Bakulin, ... arXiv preprint arXiv:2308.15395, 2023 | 7 | 2023 |
| Diagonalizable shift and filters for directed graphs based on the Jordan-Chevalley decomposition P Misiakos, C Wendler, M Püschel ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 5 | 2020 |
| Learning signals and graphs from time-series graph data with few causes P Misiakos, V Mihal, M Püschel ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 4 | 2024 |
| Learning Gene Regulatory Networks under Few Root Causes assumption. P Misiakos, C Wendler, M Püschel | 2 | 2023 |
| TropNNC: Structured Neural Network Compression Using Tropical Geometry K Fotopoulos, P Maragos, P Misiakos arXiv preprint arXiv:2409.03945, 2024 | 1 | 2024 |
| Learning Time-Varying Graphs from Data with Few Causes P Misiakos, M Püschel ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and …, 2025 | | 2025 |
| Learning DAGs and Root Causes from Time-Series Data P Misiakos, M Püschel arXiv preprint arXiv:2501.03130, 2025 | | 2025 |
Markus PüschelProfessor of Computer Science, ETH Zurich, SwitzerlandBestätigte E-Mail-Adresse bei inf.ethz.ch