I am a PhD student at the University of Toronto, advised by Jimmy Ba. I finised my MRes in Computational Statistics and Machine Learning at University College London, advised by Tim Lillicrap and Karl Friston. I am a student researcher at Google Brain.
My goal is to build intelligent machines based on concepts of the human brain, and evaluate them in complex simulations. Currently, I’m especially interested in agents that learn without rewards, model-based exploration, and variational inference.
If you have any questions, feel free to contact me at [email protected].
2018-09-05 STEVE paper accepted for oral presentation at NIPS 2018.
2018-04-12 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 unsupervised exploration in reinforcement learning. Danijar obtained his MRes at the University College London and Gatsby Unit under the supervision of Timothy Lillicrap and Karl Friston. He is also an intern at the robotics group 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.