A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music. - Adam Roberts; Jesse H. Engel; Colin Raffel; Curtis Hawthorne; Douglas Eck (ICML, 2018)

Onsets and Frames: Dual-Objective Piano Transcription. - Curtis Hawthorne; Erich Elsen; Jialin Song; Adam Roberts; Ian Simon; Colin Raffel; Jesse H. Engel; Sageev Oore; Douglas Eck (ISMIR, 2018)

Learning a Latent Space of Multitrack Measures. - Ian Simon; Adam Roberts; Colin Raffel; Jesse H. Engel; Curtis Hawthorne; Douglas Eck (CoRR, 2018)

An Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation. - Cheng-Zhi Anna Huang; Ashish Vaswani; Jakob Uszkoreit; Noam Shazeer; Curtis Hawthorne; Andrew M. Dai; Matthew D. Hoffman; Douglas Eck (CoRR, 2018)

Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset. - Curtis Hawthorne; Andriy Stasyuk; Adam Roberts; Ian Simon; Cheng-Zhi Anna Huang; Sander Dieleman; Erich Elsen; Jesse H. Engel; Douglas Eck (ICLR, 2019)

Music Transformer: Generating Music with Long-Term Structure. - Cheng-Zhi Anna Huang; Ashish Vaswani; Jakob Uszkoreit; Ian Simon; Curtis Hawthorne; Noam Shazeer; Andrew M. Dai; Matthew D. Hoffman; Monica Dinculescu; Douglas Eck (ICLR (Poster), 2019)

Approachable Music Composition with Machine Learning at Scale. - Cheng-Zhi Anna Huang; Curtis Hawthorne; Adam Roberts; Monica Dinculescu; James Wexler; Leon Hong; Jacob Howcroft (ISMIR, 2019)

The Bach Doodle: Approachable music composition with machine learning at scale. - Cheng-Zhi Anna Huang; Curtis Hawthorne; Adam Roberts; Monica Dinculescu; James Wexler; Leon Hong; Jacob Howcroft (CoRR, 2019)

Encoding Musical Style with Transformer Autoencoders. - Kristy Choi; Curtis Hawthorne; Ian Simon; Monica Dinculescu; Jesse H. Engel (ICML, 2020)

Improving Perceptual Quality of Drum Transcription with the Expanded Groove MIDI Dataset. - Lee Callender; Curtis Hawthorne; Jesse H. Engel (CoRR, 2020)

Sequence-to-Sequence Piano Transcription with Transformers. - Curtis Hawthorne; Ian Simon; Rigel Swavely; Ethan Manilow; Jesse H. Engel (ISMIR, 2021)

Symbolic Music Generation with Diffusion Models. - Gautam Mittal; Jesse H. Engel; Curtis Hawthorne; Ian Simon (ISMIR, 2021)

Improving Source Separation by Explicitly Modeling Dependencies between Sources. - Ethan Manilow; Curtis Hawthorne; Cheng-Zhi Anna Huang; Bryan Pardo; Jesse H. Engel (ICASSP, 2022)

MT3: Multi-Task Multitrack Music Transcription. - Josh Gardner 001; Ian Simon; Ethan Manilow; Curtis Hawthorne; Jesse H. Engel (ICLR, 2022)

General-purpose, long-context autoregressive modeling with Perceiver AR. - Curtis Hawthorne; Andrew Jaegle; Catalina Cangea; Sebastian Borgeaud; Charlie Nash; Mateusz Malinowski; Sander Dieleman; Oriol Vinyals; Matthew M. Botvinick; Ian Simon; Hannah Sheahan; Neil Zeghidour; et al. (ICML, 2022)

Multi-instrument Music Synthesis with Spectrogram Diffusion. - Curtis Hawthorne; Ian Simon; Adam Roberts; Neil Zeghidour; Josh Gardner 001; Ethan Manilow; Jesse H. Engel (ISMIR, 2022)

Scaling Polyphonic Transcription with Mixtures of Monophonic Transcriptions. - Ian Simon; Josh Gardner 001; Curtis Hawthorne; Ethan Manilow; Jesse H. Engel (ISMIR, 2022)

Scaling Up Models and Data with t5x and seqio. - Adam Roberts; Hyung Won Chung; Anselm Levskaya; Gaurav Mishra; James Bradbury; Daniel Andor; Sharan Narang; Brian Lester; Colin Gaffney; Afroz Mohiuddin; Curtis Hawthorne; Aitor Lewkowycz; et al. (CoRR, 2022)

The Chamber Ensemble Generator: Limitless High-Quality MIR Data via Generative Modeling. - Yusong Wu; Josh Gardner 001; Ethan Manilow; Ian Simon; Curtis Hawthorne; Jesse H. Engel (CoRR, 2022)

Continuous diffusion for categorical data. - Sander Dieleman; Laurent Sartran; Arman Roshannai; Nikolay Savinov; Yaroslav Ganin; Pierre H. Richemond; Arnaud Doucet; Robin Strudel; Chris Dyer; Conor Durkan; Curtis Hawthorne; Rémi Leblond; et al. (CoRR, 2022)

Scaling Up Models and Data with t5x and seqio. - Adam Roberts; Hyung Won Chung; Gaurav Mishra; Anselm Levskaya; James Bradbury; Daniel Andor; Sharan Narang; Brian Lester; Colin Gaffney; Afroz Mohiuddin; Curtis Hawthorne; Aitor Lewkowycz; et al. (J. Mach. Learn. Res., 2023)