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Clockwork Variational Autoencoders


Feb 20, 2021
Vaibhav Saxena, Jimmy Ba, Danijar Hafner

* 17 pages, 12 figures, 4 tables 

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Clockwork Variational Autoencoders for Video Prediction


Feb 18, 2021
Vaibhav Saxena, Jimmy Ba, Danijar Hafner

* 17 pages, 12 figures, 4 tables 

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Evaluating Agents without Rewards


Dec 21, 2020
Brendon Matusch, Jimmy Ba, Danijar Hafner

* 15 pages, 6 figures, 5 tables 

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Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning


Dec 08, 2020
Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan


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Skill Transfer via Partially Amortized Hierarchical Planning


Nov 27, 2020
Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti

* First two authors contributed equally. Preprint. NeurIPS 2020 Deep RL Workshop and under review 

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Mastering Atari with Discrete World Models


Oct 05, 2020
Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, Jimmy Ba

* 8 pages, 4 figures, 4 tables 

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Action and Perception as Divergence Minimization


Oct 05, 2020
Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl Friston, Nicolas Heess

* 14 pages, 10 figures, 2 tables 

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Sophisticated Inference


Jun 07, 2020
Karl Friston, Lancelot Da Costa, Danijar Hafner, Casper Hesp, Thomas Parr


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Planning to Explore via Self-Supervised World Models


May 12, 2020
Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak

* Videos and code at https://ramanans1.github.io/plan2explore/ 

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Dream to Control: Learning Behaviors by Latent Imagination


Dec 03, 2019
Danijar Hafner, Timothy Lillicrap, Jimmy Ba, Mohammad Norouzi

* 9 pages, 12 figures 

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Bayesian Layers: A Module for Neural Network Uncertainty


Dec 11, 2018
Dustin Tran, Michael W. Dusenberry, Mark van der Wilk, Danijar Hafner

* Presented in NeurIPS 2018 workshop Bayesian Deep Learning. Code available at https://github.com/tensorflow/tensor2tensor 

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Learning Latent Dynamics for Planning from Pixels


Dec 03, 2018
Danijar Hafner, Timothy Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson

* 10 pages, 5 figures, 1 table 

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Modulated Policy Hierarchies


Nov 30, 2018
Alexander Pashevich, Danijar Hafner, James Davidson, Rahul Sukthankar, Cordelia Schmid

* 8 pages, 5 figures 

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TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow


Oct 31, 2018
Danijar Hafner, James Davidson, Vincent Vanhoucke

* White paper, 7 pages 

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Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors


Oct 31, 2018
Danijar Hafner, Dustin Tran, Timothy Lillicrap, Alex Irpan, James Davidson

* 9 pages, 5 figures 

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Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion


Jul 04, 2018
Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee


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Sim-to-Real: Learning Agile Locomotion For Quadruped Robots


May 16, 2018
Jie Tan, Tingnan Zhang, Erwin Coumans, Atil Iscen, Yunfei Bai, Danijar Hafner, Steven Bohez, Vincent Vanhoucke

* Accompanying video: https://www.youtube.com/watch?v=lUZUr7jxoqM 

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Generative Interest Estimation for Document Recommendations


Nov 28, 2017
Danijar Hafner, Alexander Immer, Willi Raschkowski, Fabian Windheuser


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Learning Hierarchical Information Flow with Recurrent Neural Modules


Nov 04, 2017
Danijar Hafner, Alex Irpan, James Davidson, Nicolas Heess

* NIPS 2017 

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Deep Reinforcement Learning From Raw Pixels in Doom


Oct 07, 2016
Danijar Hafner

* Bachelor's thesis 

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