Jesse Engel
At Google Brain, I am performing research at the intersection of creativity and learning as part of the Magenta project. I have a UC Berkeley ^3 degree (BA, PhD, Postdoc) and my research background is diverse, including work in Astrophysics, Materials Science, Chemistry, Electrical Engineering, Computational Neuroscience, and now Machine Learning. For more details on my music and side projects check out my personal website.
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Google
Noise2Music: Text-conditioned Music Generation with Diffusion Models
Qingqing Huang
Daniel S. Park
Tao Wang
Nanxin Chen
Zhengdong Zhang
Zhishuai Zhang
Jiahui Yu
Christian Frank
William Chan
Zhifeng Chen
Wei Han
(2023)
MusicLM: Generating Music From Text
Andrea Agostinelli
Zalán Borsos
Mauro Verzetti
Antoine Caillon
Qingqing Huang
Marco Tagliasacchi
Matt Sharifi
Neil Zeghidour
Christian Frank
under review (2023)
The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling
Yusong Wu
Josh Gardner
Curtis Glenn-Macway Hawthorne
arXiv (2022)
MIDI-DDSP: Hierarchical modeling of music for detailed control
Yusong Wu
Yi Deng
Rigel Jacob Swavely
Kyle Kastner
TIm Cooijmans
Aaron Courville
ICLR 2022 (2022) (to appear)
MT3: Multi-task Multitrack Music Transcription
Josh Gardner
Curtis Glenn-Macway Hawthorne
ICLR 2022 (to appear)
Sequence-to-Sequence Piano Transcription with Transformers
Curtis Glenn-Macway Hawthorne
Rigel Jacob Swavely
ISMIR (2021) (to appear)
Tone Transfer: In-Browser Interactive Neural Audio Synthesis
Michelle Carney
Chong Li
Edwin Toh
Ping Yu
https://hai-gen2021.github.io/ (2021) (to appear)
