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 variational inference.
If you have any questions, feel free to contact me at [email protected].
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.
2018-02-14 Talk at IBM Research AI on ThalNet.
Please see my Scholar profile for a full list including article links.
Danijar Hafner is a PhD candidate at the University of Toronto under the supervision of Jimmy Ba, where he focuses on designing 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. He is also a student researcher at Google Brain. 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.