SCS Special Seminar
— 3:00pm
Location:
In Person and Virtual - ET
-
Newell-Simon 4305 and Zoom
Speaker:
GUS XIA
,
Assistant Professor in Computer ScienceComputer Science DepartmentNew York University Shanghaiand New York University Tandon
http://www.cs.cmu.edu/~gxia/
Small Tricks, Grand Design: Learning Interpretable Music Representations Using Inductive Bias
Gus has been leading the Music X Lab in developing intelligent systems that help people better compose, perform and learn music. In this talk, he will show us the importance of music representation for both humans and machines, and how to learn better music representations via the design of inductive bias. With interpretable and disentangled music representations, we can push the capability of both automated music understanding and generation to the next level. At the end of the talk, Gus will share his insights on the general form of inductive bias for music representation, as well as its connections with self-supervised learning, theoretical physics, and art creation.
—
Gus Xia is an Assistant Professor in Computer Science at NYU Shanghai. He received his Ph.D. in the Machine Learning Department at Carnegie Mellon University in 2016, and he was a Neukom Fellow at Dartmouth from 2016 to 2017. Gus is also a professional Di and Xiao (Chinese flute and vertical flute) player. He plays as a soloist in NYU Shanghai Jazz ensemble, Pitt Carpathian Ensemble , and Chinese Music Institute of Peking University, where he also served as the president and assistant conductor. Lab website. Faculty Host: Roger Dannenberg In Person and Zoom Participation. See announcement.
For More Information:
emodoono@andrew.cmu.edu