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Author

Curtis Hawthorne

Observed name: Hawthorne, Curtis
Observed institution: Google (United States)
OpenAlex ID: A5083209727
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
2018 · Roberts, Adam, Engel, Jesse, et al. · arXiv (Cornell University) · 336
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Music Transformer: Generating Music with Long-Term Structure
2019 · Cheng-Zhi Anna Huang, Ashish Vaswani, et al. · International Conference on Learning Representations · 330
Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset
2018 · Hawthorne, Curtis, Stasyuk, Andriy, et al. · arXiv (Cornell University) · 301
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Onsets and Frames: Dual-Objective Piano Transcription
2017 · Hawthorne, Curtis, Elsen, Erich, et al. · arXiv (Cornell University) · 186
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Music Transformer
2018 · Huang, Cheng-Zhi Anna, Vaswani, Ashish, et al. · arXiv (Cornell University) · 144
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Symbolic Music Generation with Diffusion Models
2021 · Mittal, Gautam, Engel, Jesse, et al. · arXiv (Cornell University) · 72
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Encoding Musical Style with Transformer Autoencoders
2019 · Choi, Kristy, Hawthorne, Curtis, et al. · arXiv (Cornell University) · 54
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An Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation
2018 · Cheng-Zhi Anna Huang, Ashish Vaswani, et al. · arXiv (Cornell University) · 54
Scaling Up Models and Data with $\texttt{t5x}$ and $\texttt{seqio}$
2022 · Roberts, Adam, Chung, Hyung Won, et al. · arXiv (Cornell University) · 46
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The Bach Doodle: Approachable music composition with machine learning at scale
2019 · Huang, Cheng-Zhi Anna, Hawthorne, Curtis, et al. · arXiv (Cornell University) · 41
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General-purpose, long-context autoregressive modeling with Perceiver AR
2022 · Hawthorne, Curtis, Jaegle, Andrew, et al. · arXiv (Cornell University) · 39
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Sequence-to-Sequence Piano Transcription with Transformers
2021 · Hawthorne, Curtis, Simon, Ian, et al. · arXiv (Cornell University) · 35
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Learning a Latent Space of Multitrack Measures
2018 · Simon, Ian, Roberts, Adam, et al. · arXiv (Cornell University) · 30
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Magenta Studio: Augmenting Creativity with Deep Learning in Ableton Live
2019 · Roberts, Adam, Engel, Jesse, et al. · Zenodo (CERN European Organization for Nuclear Research) · 28
Continuous diffusion for categorical data
2022 · Dieleman, Sander, Sartran, Laurent, et al. · arXiv (Cornell University) · 26
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Multi-instrument Music Synthesis with Spectrogram Diffusion
2022 · Hawthorne, Curtis, Simon, Ian, et al. · arXiv (Cornell University) · 22
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MT3: Multi-Task Multitrack Music Transcription
2021 · Gardner, Josh, Simon, Ian, et al. · arXiv (Cornell University) · 20
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Magenta.js: A JavaScript API for Augmenting Creativity with Deep Learning
2018 · Adam P. Roberts, Curtis Hawthorne, et al. · 19
Self-supervised Pitch Detection by Inverse Audio Synthesis
2020 · Jesse Engel, Rigel Swavely, et al. · 16
Improving Perceptual Quality of Drum Transcription with the Expanded Groove MIDI Dataset
2020 · Callender, Lee, Hawthorne, Curtis, et al. · arXiv (Cornell University) · 13
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The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling
2022 · Wu, Yusong, Gardner, Josh, et al. · arXiv (Cornell University) · 10
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Approachable Music Composition with Machine Learning at Scale.
2019 · Adam P. Roberts, Anna Huang, et al. · International Symposium/Conference on Music Information Retrieval · 5
Scaling Polyphonic Transcription with Mixtures of Monophonic Transcriptions
2022 · Simon, Ian, Gardner, Joshua, et al. · Zenodo (CERN European Organization for Nuclear Research) · 3
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Improving Source Separation by Explicitly Modeling Dependencies between Sources
2022 · Ethan Manilow, Curtis Hawthorne, et al. · IEEE International Conference on Acoustics Speech and Signal Processing · 3
Improving Source Separation by Explicitly Modeling Dependencies Between Sources
2022 · Manilow, Ethan, Hawthorne, Curtis, et al. · arXiv (Cornell University)
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Works count: 31
Citation count: 1,843
H-index: 18
I10-index: 21
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