I am a PhD student at the University of Toronto, advised by Jimmy Ba. I am also a student researcher at Google Brain in Geoffrey Hinton’s team. I finised my MRes in CSML at University College London, advised by Tim Lillicrap and Karl Friston.
My goal is to build intelligent machines based on concepts of the human brain, and evaluate them in complex simulations. Currently, I’m focusing on agents that learn without rewards, model-based reinforcement learning, and unsupervised learning.
If you have any questions, feel free to contact me at [email protected].
2019-03-01 Accepting student researchers at the Vector Institute.
2018-11-28 We organize the ICLR 2019 workshop on task-agnostic RL.
2018-09-05 STEVE paper accepted for oral presentation at NIPS 2018.
2018-04-12 Sim-to-real Minitaur paper accepted at RSS 2018.
2018-02-16 Guest lecture at Stanford CS 20 on Variational Inference in TF.
Please see my Scholar profile for a full list including article links.
Danijar Hafner is a PhD student at the University of Toronto supervised by Jimmy Ba and a student researcher in Geoffrey Hinton’s team at Google Brain. His research focuses on unsupervised learning and reinforcement learning, specifically on building agents that learn without rewards. Danijar obtained his MRes at the University College London and Gatsby Unit under the supervision of Timothy Lillicrap and Karl Friston. Danijar co-authored the book “TensorFlow for Machine Intelligence” and advises Stanford’s course “TensorFlow for Deep Learning Research”. He completed his bachelor’s thesis on deep reinforcement learning for the video game Doom at the Hasso Plattner Institute, Germany.