| Open rl benchmark: Comprehensive tracked experiments for reinforcement learning S Huang, Q Gallouédec, F Felten, A Raffin, RFJ Dossa, Y Zhao, ... arXiv preprint arXiv:2402.03046, 2024 | 19 | 2024 |
| Neural Citation Recommendation: A Reproducibility Study. M Färber, T Klein, J Sigloch Bir@ ecir, 66-74, 2020 | 19 | 2020 |
| A threat model for vehicular fog computing T Klein, T Fenn, A Katzenbach, H Teigeler, S Lins, A Sunyaev IEEE access 10, 133256-133278, 2022 | 11 | 2022 |
| Plasticity loss in deep reinforcement learning: A survey T Klein, L Miklautz, K Sidak, C Plant, S Tschiatschek arXiv preprint arXiv:2411.04832, 2024 | 9 | 2024 |
| Breaking the reclustering barrier in centroid-based deep clustering L Miklautz, T Klein, K Sidak, C Leiber, T Lang, A Shkabrii, S Tschiatschek, ... arXiv preprint arXiv:2411.02275, 2024 | 4 | 2024 |
| Active Third-Person Imitation Learning T Klein, S Weinberger, A Singla, S Tschiatschek arXiv preprint arXiv:2312.16365, 2023 | 1 | 2023 |
| Understanding and Improving Hyperbolic Deep Reinforcement Learning T Klein, T Lang, A Shkabrii, A Sturm, K Sidak, L Miklautz, C Plant, Y Velaj, ... arXiv preprint arXiv:2512.14202, 2025 | | 2025 |
| Active Third-Person Imitation T Klein, S Weinberger, A Singla, S Tschiatschek | | 2023 |
| ReSL: Enhancing Deep Clustering Through Reset-based Self-Labeling A Shkabrii, T Klein, L Miklautz, S Tschiatschek, C Plant Scaling Self-Improving Foundation Models without Human Supervision, 0 | | |
Sebastian TschiatschekUniversity of ViennaVerified email at univie.ac.at
