| Audio set: An ontology and human-labeled dataset for audio events JF Gemmeke, DPW Ellis, D Freedman, A Jansen, W Lawrence, RC Moore, ... 2017 IEEE international conference on acoustics, speech and signal …, 2017 | 2166 | 2017 |
| Self-supervised gans via auxiliary rotation loss T Chen, X Zhai, M Ritter, M Lucic, N Houlsby Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 265 | 2019 |
| High-fidelity image generation with fewer labels M Lučić, M Tschannen, M Ritter, X Zhai, O Bachem, S Gelly International conference on machine learning, 4183-4192, 2019 | 134 | 2019 |
| Flax: A neural network library and ecosystem for JAX, 2020 J Heek, A Levskaya, A Oliver, M Ritter, B Rondepierre, A Steiner, ... URL http://github. com/google/flax 1, 2020 | 75 | 2020 |
| Continental-scale building detection from high resolution satellite imagery W Sirko, S Kashubin, M Ritter, A Annkah, YSE Bouchareb, Y Dauphin, ... arXiv preprint arXiv:2107.12283, 2021 | 60 | 2021 |
| Flax: A neural network library and ecosystem for JAX J Heek, A Levskaya, A Oliver, M Ritter, B Rondepierre, A Steiner, ... Version 0.3 3, 14-26, 2020 | 53 | 2020 |
| Self-supervised learning of video-induced visual invariances M Tschannen, J Djolonga, M Ritter, A Mahendran, N Houlsby, S Gelly, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 52 | 2020 |
| Scaling up models and data with t5x and seqio A Roberts, HW Chung, A Levskaya, G Mishra, J Bradbury, D Andor, ... arXiv preprint arXiv:2203.17189 13, 2022 | 37 | 2022 |
| Self-supervised generative adversarial networks T Chen, X Zhai, M Ritter, M Lucic, N Houlsby arXiv preprint arXiv:1811.11212 2, 2018 | 21 | 2018 |
| Now playing: Continuous low-power music recognition BA y Arcas, B Gfeller, R Guo, K Kilgour, S Kumar, J Lyon, J Odell, M Ritter, ... arXiv preprint arXiv:1711.10958 [cs, eess], 2017 | 21 | 2017 |
| Now playing: Continuous low-power music recognition B Gfeller, R Guo, K Kilgour, S Kumar, J Lyon, J Odell, M Ritter, D Roblek, ... arXiv preprint arXiv:1711.10958, 2017 | 17 | 2017 |
| Now playing: Continuous low-power music recognition B Gfeller, R Guo, K Kilgour, S Kumar, J Lyon, J Odell, M Ritter, D Roblek, ... arXiv preprint arXiv:1711.10958, 2017 | 17 | 2017 |
| Representation learning from videos in-the-wild: An object-centric approach R Romijnders, A Mahendran, M Tschannen, J Djolonga, M Ritter, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 7 | 2021 |
| Identifying music as a particular song D Roblek, BH Aguera-Arcas, TW Hume, MK Ritter, BC Barbello, KI Kilgour, ... US Patent 10,761,802, 2020 | 6 | 2020 |
| Training deep neural networks for reverberation robust speech recognition M Ritter, M Müller, S Stüker, F Metze, A Waibel Speech Communication; 12. ITG Symposium, 1-5, 2016 | 5 | 2016 |
| Determining that audio includes music and then identifying the music as a particular song D Roblek, BH Aguera-Arcas, TW Hume, MK Ritter, BC Barbello, KI Kilgour, ... US Patent 10,809,968, 2020 | 4 | 2020 |
| Neural Network Architectures for Reverberated Lecture Speech Recognition M Ritter Informatics Institute, 2016 | 1 | 2016 |
| Scaling Up Models and Data with and A Roberts, HW Chung, A Levskaya, G Mishra, J Bradbury, D Andor, ... arXiv preprint arXiv:2203.17189, 2022 | | 2022 |
| Determining that audio includes music and then identifying the music as a particular song D Roblek, BH Aguera-Arcas, TW Hume, MK Ritter, BC Barbello, KI Kilgour, ... US Patent 11,256,472, 2022 | | 2022 |
| 用更少的标签生成高保真的图像 M Lucic, M Tschannen, M Ritter, X Zhai, O Bachem, S Gelly arXiv preprint arXiv:1903.02271, 2019 | | 2019 |
