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Chris Donahue
Chris Donahue
Research Scientist, Google Magenta
Verified email at cs.stanford.edu - Homepage
Title
Cited by
Cited by
Year
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
6562021
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
3682019
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
2112018
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
1182018
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
1152020
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
862019
Dance Dance Convolution
C Donahue, ZC Lipton, J McAuley
(ICML 2017) International Conference on Machine Learning, 2017
492017
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
362021
Piano Genie
C Donahue, I Simon, S Dieleman
(ACM IUI 2019) ACM Conference on Intelligent User Interfaces, 2018
362018
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
322022
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
232018
Expediting TTS Synthesis with Adversarial Vocoding
P Neekhara, C Donahue, M Puckette, S Dubnov, J McAuley
INTERSPEECH 2019, 2019
212019
Towards realistic MIDI instrument synthesizers
R Castellon, C Donahue, P Liang
(NeurIPS Workshop 2020) NeurIPS Workshop on Machine Learning for Creativity …, 2020
72020
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
22021
Sheet Sage: Lead sheets from music audio
C Donahue, P Liang
(ISMIR LBD 2021) ISMIR Late-breaking demo session, 2021
22021
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
22017
Applications of Genetic Programming to Digital Audio Synthesis
C Donahue
Undergraduate Thesis, The University of Texas at Austin, 2013
22013
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