Before this I was supervised by Giuseppe Carenini in the Laboratory for Computational Intelligence where I completed my M.Sc. in artificial intelligence. I have also had the good fortune of working with Siamak Ravanbakhsh, Emtiyaz Khan, and Colin Gay in deep learning, approximate bayesian inference, and particle physics, respectively.
My CV is here.
|Dec 12, 2020||We received best paper award at the NeurIPS Workshop on Deep Learning through Information Geometry! Check out Annealed Importance Sampling with q-Paths where we generalize the 1-d geometric path commonly used in Annealed Importance Sampling into a 2-d plane. Poster, code.|
|Dec 10, 2020||Excited about this one! Gaussian Process Bandit Optimization of the Thermodynamic Variational Objective where we address the problem of scheduling in the TVO using Gaussian Processes and Bandits!|
|Jul 6, 2020||Excited to announce our new ICML paper All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference with the brilliant Rob Brekelmans (@brekelmaniac)!|
|Mar 30, 2020||New preprint! Planning as Inference in Epidemiological Models|
|Feb 24, 2020||Our paper Improved Few-Shot Visual Classification accepted at CVPR 2020 - great work Peyman!|
Department of Computer Science
University of British Columbia
X725-2366 Main Mall