I am a second-year graduate student in the EECS department at MIT and a member of CSAIL and the Machine Learning group.
My research interests are in deep learning, theory and representation learning. I am advised by Stefanie Jegelka.
I studied mathematics and computer science as an undergraduate at University of British Columbia (UBC) in the beautiful city of Vancouver, where I was fortunate to be advised by Nick Harvey.
Aside from computer science, I enjoy artsy and adventurous activities, such as trading, Mahjong (gambling), novel writing, hunting, and people watching. I like to come up with general theory for everything. Currently, I am working on an ambitious project on creating a general framework for finance, politics and sociology.
- Deep depression, dear theoretical alchemist.
Email me if you have any questions about my papers or code, or if you would like to collaborate with me.
- Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, Stefanie Jegelka.
International Conference on Machine Learning (ICML) 2018. Long talk.
[arXiv] [Code (soon)]
- Distributional Adversarial Networks
Chengtao Li, David Alvarez-Melis, Keyulu Xu, Stefanie Jegelka, Suvrit Sra.
International Conference on Learning Representations workshop track (ICLR) 2018.
- Generating Random Spanning Trees via Fast Matrix Multiplication
Nicholas J. A. Harvey and Keyulu Xu.
Latin American Theoretical Informatics Symposium (LATIN) 2016.
I have lived and worked in some of the most exciting cities in the world -- Vancouver, NYC, Tokyo and Shanghai.
Some recent talks by Keyulu, with video if available.
- Generating Random Spanning Trees via Fast Matrix Multiplication, at LATIN 2016, Ensenada, Mexico. [PPTX]