I am an MRes student in Computational Statistics and Machine Learning at University College London advised by Tim Lillicrap and Karl Friston. I am also a student researcher with Vincent Vanhoucke at Google Brain’s robotics team.
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 model based exploration, Bayesian reinforcement learning, and temporal abstraction.
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 graduate student at University College London under the supervision of Tim Lillicrap and Karl Friston. He is also an intern with the robotics group at Google Brain, where he developed the brain-inspired sequence model ThalNet and the reinforcement learning library TensorFlow Agents. Danijar Hafner co-authored the book “TensorFlow for Machine Intelligence” and guest lectured in 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.