| Adversarial Audio Synthesis C Donahue, J McAuley, M Puckette (ICLR 2019) International Conference on Learning Representations, 2019 | 666* | 2019 |
| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv:2108.07258, 2021 | 656 | 2021 |
| GANSynth: Adversarial neural audio synthesis J Engel, KK Agrawal, S Chen, I Gulrajani, C Donahue, A Roberts (ICLR 2019) International Conference on Learning Representations, 2019 | 368 | 2019 |
| Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition C Donahue, B Li, R Prabhavalkar (ICASSP 2018) International Conference on Acoustics, Speech, and Signal …, 2018 | 211 | 2018 |
| Semantically Decomposing the Latent Spaces of Generative Adversarial Networks C Donahue, ZC Lipton, A Balsubramani, J McAuley (ICLR 2018) International Conference on Learning Representations, 2018 | 118 | 2018 |
| Enabling Language Models to Fill in the Blanks C Donahue, M Lee, P Liang (ACL 2020) Annual Conference of the Association for Computational Linguistics, 2020 | 115 | 2020 |
| LakhNES: Improving multi-instrumental music generation with cross-domain pre-training C Donahue, HH Mao, YE Li, GW Cottrell, J McAuley (ISMIR 2019) International Society for Music Information Retrieval Conference, 2019 | 86 | 2019 |
| Dance Dance Convolution C Donahue, ZC Lipton, J McAuley (ICML 2017) International Conference on Machine Learning, 2017 | 49 | 2017 |
| Codified audio language modeling learns useful representations for music information retrieval R Castellon, C Donahue, P Liang (ISMIR 2021) International Society for Music Information Retrieval Conference, 2021 | 36 | 2021 |
| Piano Genie C Donahue, I Simon, S Dieleman (ACM IUI 2019) ACM Conference on Intelligent User Interfaces, 2018 | 36 | 2018 |
| It's Raw! Audio Generation with State-Space Models K Goel, A Gu, C Donahue, C Ré (ICML 2022) International Conference on Machine Learning, 2022 | 32 | 2022 |
| The NES Music Database: A multi-instrumental dataset with expressive performance attributes C Donahue, HH Mao, J McAuley (ISMIR 2018) International Society for Music Information Retrieval Conference, 2018 | 23 | 2018 |
| Expediting TTS Synthesis with Adversarial Vocoding P Neekhara, C Donahue, M Puckette, S Dubnov, J McAuley INTERSPEECH 2019, 2019 | 21 | 2019 |
| Towards realistic MIDI instrument synthesizers R Castellon, C Donahue, P Liang (NeurIPS Workshop 2020) NeurIPS Workshop on Machine Learning for Creativity …, 2020 | 7 | 2020 |
| Extended Convolution Techniques for Cross-Synthesis C Donahue, T Erbe, M Puckette (ICMC 2016) International Computer Music Conference, 2016 | 7* | 2016 |
| SWORDS ⚔: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality M Lee, C Donahue, R Jia, A Iyabor, P Liang (NAACL 2021) Conference of the North American Chapter of the Association for …, 2021 | 3* | 2021 |
| Towards Automatic Instrumentation by Learning to Separate Parts in Symbolic Multitrack Music HW Dong, C Donahue, T Berg-Kirkpatrick, J McAuley (ISMIR 2021) International Society for Music Information Retrieval Conference, 2021 | 2 | 2021 |
| Sheet Sage: Lead sheets from music audio C Donahue, P Liang (ISMIR LBD 2021) ISMIR Late-breaking demo session, 2021 | 2 | 2021 |
| Disentangled Representations of Style and Content for Visual Art with Generative Adversarial Networks C Donahue, J McAuley (NIPS Workshop 2017) NIPS Workshop on Machine Learning for Creativity and …, 2017 | 2 | 2017 |
| Applications of Genetic Programming to Digital Audio Synthesis C Donahue Undergraduate Thesis, The University of Texas at Austin, 2013 | 2 | 2013 |
Julian McAuleyProfessor, UC San DiegoVerified email at eng.ucsd.edu
