| On Identifiability in Transformers G Brunner, Y Liu, D Pascual, O Richter, M Ciaramita, R Wattenhofer International Conference on Learning Representations (ICLR), 2019, 2019 | 220* | 2019 |
| MIDI-VAE: Modeling dynamics and instrumentation of music with applications to style transfer G Brunner, A Konrad, Y Wang, R Wattenhofer Proc. Int. Society for Music Information Retrieval Conf, 2018 | 166 | 2018 |
| Symbolic Music Genre Transfer with CycleGAN G Brunner, Y Wang, R Wattenhofer, S Zhao | 104 | 2018 |
| Recognition and repetition counting for complex physical exercises with deep learning A Soro, G Brunner, S Tanner, R Wattenhofer Sensors 19 (3), 714, 2019 | 98 | 2019 |
| The urban last mile problem: Autonomous drone delivery to your balcony G Brunner, B Szebedy, S Tanner, R Wattenhofer 2019 international conference on unmanned aircraft systems (icuas), 1005-1012, 2019 | 91 | 2019 |
| JamBot: Music theory aware chord based generation of polyphonic music with LSTMs G Brunner, Y Wang, R Wattenhofer, J Wiesendanger 2017 IEEE 29th international conference on tools with artificial …, 2017 | 79 | 2017 |
| 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 | 48 | 2018 |
| Swimming style recognition and lap counting using a smartwatch and deep learning G Brunner, D Melnyk, B Sigfússon, R Wattenhofer Proceedings of the 2019 ACM International Symposium on Wearable Computers, 23-31, 2019 | 38 | 2019 |
| Telling BERT's full story: from Local Attention to Global Aggregation D Pascual, G Brunner, R Wattenhofer arXiv preprint arXiv:2004.05916, 2020 | 24 | 2020 |
| Attentive Multi-Task Deep Reinforcement Learning G Brunner, T Bräm, O Richter, R Wattenhofer European Conference on Machine Learning and Principles and Practice of …, 2019 | 23* | 2019 |
| Of non-linearity and commutativity in bert S Zhao, D Pascual, G Brunner, R Wattenhofer 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 12 | 2021 |
| Monaural Music Source Separation using a ResNet Latent Separator Network G Brunner, N Naas, S Palsson, O Richter, R Wattenhofer | 9 | 2019 |
| Natural language multitasking: analyzing and improving syntactic saliency of hidden representations G Brunner, Y Wang, R Wattenhofer, M Weigelt NeurIPS Workshop on Learning Disentangled Features: from Perception to Control, 2018 | 9 | 2018 |
| Disentangling the latent space of (variational) autoencoders for NLP G Brunner, Y Wang, R Wattenhofer, M Weigelt Advances in Computational Intelligence Systems: Contributions Presented at …, 2019 | 8 | 2019 |
| Neural Symbolic Music Genre Transfer Insights G Brunner, M Moayeri, O Richter, R Wattenhofer, C Zhang 12th International Workshop on Machine Learning and Music (MML 2019), 2019 | 6 | 2019 |
| 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 |
| Towards measuring real-world performance of android devices P Bissig, G Brunner, F Gubler, R Wattenhofer, A Zingg 2018 IEEE/ACS 15th International Conference on Computer Systems and …, 2018 | 1 | 2018 |
| Medley2K: A Dataset of Medley Transitions L Faber, S Luck, D Pascual, A Roth, G Brunner, R Wattenhofer arXiv preprint arXiv:2008.11159, 2020 | | 2020 |
| Applications of Deep Learning for Sequential Data: Music, Human Activity and Language G Brunner ETH Zurich, 2020 | | 2020 |
| 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 Zurich在 ethz.ch 的电子邮件经过验证
