The Canadian Society of Information Theory has launched an online reading group, the Canadian Student Reading Group on Data Science, for students to get together studying and discussing modern and classical materials on Data Science, and for students in Canada to develop active academic and social interactions. The Fall 2021 season of the study group features “deep generative models”, many thanks to the organizers of this event, Professor Lele Wang, Renjie Liao, Christos Thrampoulidis, and Xiaoxiao Li.
Starting from September 20, the study group will meet every week on zoom for 1.5 hours. Each time, one person will lead the discussion of one paper in the area of deep generative models. You can take a look at the detailed paper list. These are the papers that the group plans to read, in addition to two reference courses from Stanford and Berkeley on Deep Generative Models.
Meeting time: Mondays 5:00 pm – 6:30 pm Pacific Time or 8:00 pm – 9.30 pm Eastern Time (starting Sep. 20, 2021) Zoom link:https://ubc.zoom.us/j/69862347055?pwd=R3ZGTVhDSGRXcFB6VDk1TDlyNHkrZz09 Meeting ID: 698 6234 7055 Passcode: 037245
All students in Canadian Universities are welcome to participate. Faculty members are also welcome to join the discussion. If you are interested in joining the reading group, please sign up for the reading group here; you are also welcome to volunteer to present a paper; see the presentation schedule here. For those who signed up, the study group organizers will add you to a Slack channel, which will be used for posting related materials, sending announcements, as well as having technical discussions.
We looking forward to seeing you soon in the reading group. Please also feel free to forward this message to your friends, colleagues, and students who may be interested.
Yongyi Mao, PhD
Canadian Society of Information Theory
University of Ottawa
School of Electrical Engineering and Computer Science