Probabilistic Routing for On-Street Parking Search. - Tobias Arndt; Danijar Hafner; Thomas Kellermeier; Simon Krogmann; Armin Razmjou; Martin S. Krejca; Ralf Rothenberger; Tobias Friedrich 001 (ESA, 2016)

Deep Reinforcement Learning From Raw Pixels in Doom. - Danijar Hafner (CoRR, 2016)

Learning Hierarchical Information Flow with Recurrent Neural Modules. - Danijar Hafner; Alexander Irpan; James Davidson; Nicolas Heess (NIPS, 2017)

TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow. - Danijar Hafner; James Davidson; Vincent Vanhoucke (CoRR, 2017)

Generative Interest Estimation for Document Recommendations. - Danijar Hafner; Alexander Immer; Willi Raschkowski; Fabian Windheuser (CoRR, 2017)

Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion. - Jacob Buckman; Danijar Hafner; George Tucker; Eugene Brevdo; Honglak Lee (NeurIPS, 2018)

Sim-to-Real: Learning Agile Locomotion For Quadruped Robots. - Jie Tan 001; Tingnan Zhang; Erwin Coumans; Atil Iscen; Yunfei Bai; Danijar Hafner; Steven Bohez; Vincent Vanhoucke (Robotics: Science and Systems, 2018)

Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors. - Danijar Hafner; Dustin Tran; Alex Irpan; Timothy P. Lillicrap; James Davidson (CoRR, 2018)

Modulated Policy Hierarchies. - Alexander Pashevich; Danijar Hafner; James Davidson; Rahul Sukthankar; Cordelia Schmid (CoRR, 2018)

Disorders of Artificial Awareness. - Thomas Parr; Danijar Hafner; Karl J. Friston (AAAI Spring Symposium: Towards Conscious AI Systems, 2019)

Learning Latent Dynamics for Planning from Pixels. - Danijar Hafner; Timothy P. Lillicrap; Ian Fischer; Ruben Villegas; David Ha; Honglak Lee; James Davidson (ICML, 2019)

Bayesian Layers: A Module for Neural Network Uncertainty. - Dustin Tran; Mike Dusenberry; Mark van der Wilk; Danijar Hafner (NeurIPS, 2019)

Noise Contrastive Priors for Functional Uncertainty. - Danijar Hafner; Dustin Tran; Timothy P. Lillicrap; Alex Irpan; James Davidson (UAI, 2019)

Routing for on-street parking search using probabilistic data. - Tobias Friedrich 001; Martin S. Krejca; Ralf Rothenberger; Tobias Arndt; Danijar Hafner; Thomas Kellermeier; Simon Krogmann; Armin Razmjou (AI Commun., 2019)

Dream to Control: Learning Behaviors by Latent Imagination. - Danijar Hafner; Timothy P. Lillicrap; Jimmy Ba; Mohammad Norouzi 002 (ICLR, 2020)

Planning to Explore via Self-Supervised World Models. - Ramanan Sekar; Oleh Rybkin; Kostas Daniilidis; Pieter Abbeel; Danijar Hafner; Deepak Pathak (ICML, 2020)

Action and Perception as Divergence Minimization. - Danijar Hafner; Pedro A. Ortega; Jimmy Ba; Thomas Parr; Karl J. Friston; Nicolas Heess (CoRR, 2020)

Skill Transfer via Partially Amortized Hierarchical Planning. - Kevin Xie; Homanga Bharadhwaj; Danijar Hafner; Animesh Garg; Florian Shkurti (CoRR, 2020)

Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning. - Mohammad Babaeizadeh; Mohammad Taghi Saffar; Danijar Hafner; Harini Kannan; Chelsea Finn; Sergey Levine; Dumitru Erhan (CoRR, 2020)

Evaluating Agents without Rewards. - Brendon Matusch; Jimmy Ba; Danijar Hafner (CoRR, 2020)

Mastering Atari with Discrete World Models. - Danijar Hafner; Timothy P. Lillicrap; Mohammad Norouzi 002; Jimmy Ba (ICLR, 2021)

Latent Skill Planning for Exploration and Transfer. - Kevin Xie; Homanga Bharadhwaj; Danijar Hafner; Animesh Garg; Florian Shkurti (ICLR, 2021)

Discovering and Achieving Goals via World Models. - Russell Mendonca; Oleh Rybkin; Kostas Daniilidis; Danijar Hafner; Deepak Pathak (NeurIPS, 2021)

Information is Power: Intrinsic Control via Information Capture. - Nicholas Rhinehart; Jenny Wang; Glen Berseth; John D. Co-Reyes; Danijar Hafner; Chelsea Finn; Sergey Levine (NeurIPS, 2021)

Clockwork Variational Autoencoders. - Vaibhav Saxena; Jimmy Ba; Danijar Hafner (NeurIPS, 2021)

Sophisticated Inference. - Karl J. Friston; Lancelot Da Costa; Danijar Hafner; Casper Hesp; Thomas Parr (Neural Comput., 2021)

Masked World Models for Visual Control. - Younggyo Seo; Danijar Hafner; Hao Liu 055; Fangchen Liu; Stephen James; Kimin Lee; Pieter Abbeel (CoRL, 2022)

DayDreamer: World Models for Physical Robot Learning. - Philipp Wu; Alejandro Escontrela; Danijar Hafner; Pieter Abbeel; Ken Goldberg (CoRL, 2022)

Benchmarking the Spectrum of Agent Capabilities. - Danijar Hafner (ICLR, 2022)

Deep Hierarchical Planning from Pixels. - Danijar Hafner; Kuang-Huei Lee; Ian Fischer; Pieter Abbeel (NeurIPS, 2022)

Learning Robust Dynamics through Variational Sparse Gating. - Arnav Kumar Jain; Shivakanth Sujit; Shruti Joshi; Vincent Michalski; Danijar Hafner; Samira Ebrahimi Kahou (NeurIPS, 2022)

Temporally Consistent Video Transformer for Long-Term Video Prediction. - Wilson Yan; Danijar Hafner; Stephen James; Pieter Abbeel (CoRR, 2022)

Evaluating Long-Term Memory in 3D Mazes. - Jurgis Pasukonis; Timothy P. Lillicrap; Danijar Hafner (ICLR, 2023)

Temporally Consistent Transformers for Video Generation. - Wilson Yan; Danijar Hafner; Stephen James; Pieter Abbeel (ICML, 2023)

Video Prediction Models as Rewards for Reinforcement Learning. - Alejandro Escontrela; Ademi Adeniji; Wilson Yan; Ajay Jain; Xue Bin Peng; Ken Goldberg; Youngwoon Lee; Danijar Hafner; Pieter Abbeel (NeurIPS, 2023)

Mastering Diverse Domains through World Models. - Danijar Hafner; Jurgis Pasukonis; Jimmy Ba; Timothy P. Lillicrap (CoRR, 2023)

Learning to Model the World With Language. - Jessy Lin; Yuqing Du; Olivia Watkins; Danijar Hafner; Pieter Abbeel; Dan Klein 001; Anca D. Dragan (ICML, 2024)

Embodied Intelligence Through World Models - Danijar Hafner (2024)

One Step Diffusion via Shortcut Models. - Kevin Frans; Danijar Hafner; Sergey Levine; Pieter Abbeel (ICLR, 2025)

Mastering diverse control tasks through world models. - Danijar Hafner; Jurgis Pasukonis; Jimmy Ba; Timothy P. Lillicrap (Nat., 2025)