| Bridging the gap to real-world object-centric learning M Seitzer, M Horn, A Zadaianchuk, D Zietlow, T Xiao, CJ Simon-Gabriel, ... International Conference on Learning Representations (ICLR) 2023, 2022 | 92 | 2022 |
| Unsupervised semantic segmentation with self-supervised object-centric representations A Zadaianchuk, M Kleindessner, Y Zhu, F Locatello, T Brox International Conference on Learning Representations (ICLR) 2023, 2022 | 51 | 2022 |
| Self-supervised Visual Reinforcement Learning with Object-centric Representations A Zadaianchuk, M Seitzer, G Martius International Conference on Learning Representations (ICLR) 2021, 2021 | 37 | 2021 |
| Self-supervised reinforcement learning with independently controllable subgoals A Zadaianchuk, G Martius, F Yang Conference on Robot Learning (CoRL) 2021, 384-394, 2022 | 18 | 2022 |
| Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities A Zadaianchuk, M Seitzer, G Martius Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS …, 2023 | 16 | 2023 |
| A real-robot dataset for assessing transferability of learned dynamics models D Agudelo-Espana, A Zadaianchuk, P Wenk, A Garg, J Akpo, ... International Conference on Robotics and Automation (ICRA), 2020, 8151-8157, 2020 | 9 | 2020 |
| Zero-Shot Object-Centric Representation Learning A Didolkar, A Zadaianchuk, A Goyal, M Mozer, Y Bengio, G Martius, ... arXiv preprint arXiv:2408.09162, 2024 | | 2024 |
| Discovering and Using Structure in Autonomous Machine Learning A Zadaianchuk ETH Zurich, 2024 | | 2024 |
| SENSEI: Semantic Exploration Guided by Foundation Models to Learn Versatile World Models C Sancaktar, C Gumbsch, A Zadaianchuk, P Kolev, G Martius Workshop on Training Agents with Foundation Models at RLC 2024, 2024 | | 2024 |
| Online Step Size Adaptation for Stochastic Optimization A Zadaianchuk Eberhard-Karls-Universität Tübingen, 2018 | | 2018 |
Georg MartiusUniversity of Tübingen and Max Planck Institute for Intelligent Systems在 uni-tuebingen.de 的电子邮件经过验证
