Machine Learning of Jazz Grammars. - Jon Gillick; Kevin Tang; Robert M. Keller (Comput. Music. J., 2010)

Estimating the Date of First Publication in a Large-Scale Digital Library. - David Bamman; Michelle Carney; Jon Gillick; Cody Hennesy; Vijitha Sridhar (JCDL, 2017)

Capturing, Representing, and Interacting with Laughter. - Kimiko Ryokai; Elena Durán-López; Noura Howell; Jon Gillick; David Bamman (CHI, 2018)

Please Clap: Modeling Applause in Campaign Speeches. - Jon Gillick; David Bamman (NAACL-HLT, 2018)

Learning to Groove with Inverse Sequence Transformations. - Jon Gillick; Adam Roberts; Jesse H. Engel; Douglas Eck; David Bamman (ICML, 2019)

Estimating Unobserved Audio Features for Target-Based Orchestration. - Jon Gillick; Carmine-Emanuele Cella; David Bamman (ISMIR, 2019)

Breaking Speech Recognizers to Imagine Lyrics. - Jon Gillick; David Bamman (CoRR, 2019)

Attending to Long-Distance Document Context for Sequence Labeling. - Matthew Jörke; Jon Gillick; Matthew Sims; David Bamman (EMNLP (Findings), 2020)

Robust Laughter Detection in Noisy Environments. - Jon Gillick; Wesley Deng; Kimiko Ryokai; David Bamman (Interspeech, 2021)

What to Play and How to Play it: Guiding Generative Music Models with Multiple Demonstrations. - Jon Gillick; David Bamman (NIME, 2021)

Drumroll Please: Modeling Multi-Scale Rhythmic Gestures with Flexible Grids. - Jon Gillick; Joshua Yang; Carmine-Emanuele Cella; David Bamman (Trans. Int. Soc. Music. Inf. Retr., 2021)

Creating and Collecting Meaningful Musical Material with Machine Learning - Jon Gillick (2022)