| On identifiability in transformers G Brunner, Y Liu, D Pascual, O Richter, M Ciaramita, R Wattenhofer arXiv preprint arXiv:1908.04211, 2019 | 236* | 2019 |
| Teaching a machine to read maps with deep reinforcement learning G Brunner, O Richter, Y Wang, R Wattenhofer Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 53 | 2018 |
| Attentive multi-task deep reinforcement learning T Bräm, G Brunner, O Richter, R Wattenhofer Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 24 | 2020 |
| Normalized attention without probability cage O Richter, R Wattenhofer arXiv preprint arXiv:2005.09561, 2020 | 19 | 2020 |
| TreeConnect: A sparse alternative to fully connected layers O Richter, R Wattenhofer 2018 IEEE 30th International Conference on Tools with Artificial …, 2018 | 15 | 2018 |
| Monaural music source separation using a resnet latent separator network G Brunner, N Naas, S Palsson, O Richter, R Wattenhofer 2019 IEEE 31st International Conference on Tools with Artificial …, 2019 | 10 | 2019 |
| Local checkability in dynamic networks KT Foerster, O Richter, J Seidel, R Wattenhofer Proceedings of the 18th International Conference on Distributed Computing …, 2017 | 8 | 2017 |
| Word2Course: Creating interactive courses from as little as a keyword S Foucher, D Pascual, O Richter, R Wattenhofer CSEDU: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON COMPUTER …, 2022 | 6 | 2022 |
| Unsupervised task clustering for multi-task reinforcement learning J Ackermann, O Richter, R Wattenhofer Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 6 | 2021 |
| Neural symbolic music genre transfer insights G Brunner, M Moayeri, O Richter, R Wattenhofer, C Zhang Machine Learning and Knowledge Discovery in Databases: International …, 2020 | 6 | 2020 |
| Using state predictions for value regularization in curiosity driven deep reinforcement learning G Brunner, M Fritsche, O Richter, R Wattenhofer 2018 IEEE 30th International Conference on Tools with Artificial …, 2018 | 6 | 2018 |
| Wikiflash: Generating flashcards from wikipedia articles Y Cheng, Y Ding, S Foucher, D Pascual, O Richter, M Volk, R Wattenhofer Neural Information Processing: 28th International Conference, ICONIP 2021 …, 2021 | 5 | 2021 |
| Improving brain decoding methods and evaluation D Pascual, B Egressy, N Affolter, Y Cai, O Richter, R Wattenhofer ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 4 | 2022 |
| The Frechet Distance of training and test distribution predicts the generalization gap J Zilly, H Zilly, O Richter, R Wattenhofer, A Censi, E Frazzoli | 4 | 2019 |
| Learning policies through quantile regression O Richter, R Wattenhofer arXiv preprint arXiv:1906.11941, 2019 | 2 | 2019 |
| Automating rigid origami design J Geiger, K Martinkus, O Richter, R Wattenhofer arXiv preprint arXiv:2211.13219, 2022 | 1 | 2022 |
| Learning algorithms with self-play: A new approach to the distributed directory problem P Khanchandani, O Richter, L Rusch, R Wattenhofer 2021 IEEE 33rd International Conference on Tools with Artificial …, 2021 | 1 | 2021 |
| Learning Lower Bounds for Graph Exploration With Reinforcement Learning J Elmiger, L Faber, P Khanchandani, OP Richter, R Wattenhofer Learning Meets Combinatorial Algorithms at NeurIPS2020, 2020 | 1 | 2020 |
| Architectural Considerations for Deep Reinforcement Learning O Richter ETH Zurich, 2022 | | 2022 |
| Tunnel Vision Attack on IMPALA-Questioning the Robustness of Reinforcement Learning Agents J Bolick, G Brunner, O Richter, R Wattenhofer Proceedings of the Workshop on Safety and Robustness in Decision Making at …, 2019 | | 2019 |
Roger WattenhoferETH ZurichEmail verificata su ethz.ch