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ORCIDDanijar Hafner
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2020 – today
- 2024
[c24]Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca D. Dragan:
Learning to Model the World With Language. ICML 2024- 2023
- [c23]Jurgis Pasukonis, Timothy P. Lillicrap, Danijar Hafner:
Evaluating Long-Term Memory in 3D Mazes. ICLR 2023 - [c22]Wilson Yan, Danijar Hafner, Stephen James, Pieter Abbeel:
Temporally Consistent Transformers for Video Generation. ICML 2023: 39062-39098 - [c21]Alejandro Escontrela, Ademi Adeniji, Wilson Yan, Ajay Jain, Xue Bin Peng, Ken Goldberg, Youngwoon Lee, Danijar Hafner, Pieter Abbeel:
Video Prediction Models as Rewards for Reinforcement Learning. NeurIPS 2023 - [i31]Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, Timothy P. Lillicrap:
Mastering Diverse Domains through World Models. CoRR abs/2301.04104 (2023) - [i30]Alejandro Escontrela, Ademi Adeniji, Wilson Yan, Ajay Jain, Xue Bin Peng, Ken Goldberg, Youngwoon Lee, Danijar Hafner, Pieter Abbeel:
Video Prediction Models as Rewards for Reinforcement Learning. CoRR abs/2305.14343 (2023) - [i29]Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca D. Dragan:
Learning to Model the World with Language. CoRR abs/2308.01399 (2023) - 2022
- [c20]Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel:
Masked World Models for Visual Control. CoRL 2022: 1332-1344 - [c19]Philipp Wu, Alejandro Escontrela, Danijar Hafner, Pieter Abbeel, Ken Goldberg:
DayDreamer: World Models for Physical Robot Learning. CoRL 2022: 2226-2240 - [c18]Danijar Hafner:
Benchmarking the Spectrum of Agent Capabilities. ICLR 2022 - [c17]Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel:
Deep Hierarchical Planning from Pixels. NeurIPS 2022 - [c16]Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou:
Learning Robust Dynamics through Variational Sparse Gating. NeurIPS 2022 - [i28]Danijar Hafner, Kuang-Huei Lee, Ian Fischer, Pieter Abbeel:
Deep Hierarchical Planning from Pixels. CoRR abs/2206.04114 (2022) - [i27]Philipp Wu, Alejandro Escontrela, Danijar Hafner, Ken Goldberg, Pieter Abbeel:
DayDreamer: World Models for Physical Robot Learning. CoRR abs/2206.14176 (2022) - [i26]Younggyo Seo, Danijar Hafner, Hao Liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel:
Masked World Models for Visual Control. CoRR abs/2206.14244 (2022) - [i25]Wilson Yan, Danijar Hafner, Stephen James, Pieter Abbeel:
Temporally Consistent Video Transformer for Long-Term Video Prediction. CoRR abs/2210.02396 (2022) - [i24]Arnav Kumar Jain, Shivakanth Sujit, Shruti Joshi, Vincent Michalski, Danijar Hafner, Samira Ebrahimi Kahou:
Learning Robust Dynamics through Variational Sparse Gating. CoRR abs/2210.11698 (2022) - [i23]Jurgis Pasukonis, Timothy P. Lillicrap, Danijar Hafner:
Evaluating Long-Term Memory in 3D Mazes. CoRR abs/2210.13383 (2022) - 2021
- [j2]Karl J. Friston
, Lancelot Da Costa, Danijar Hafner, Casper Hesp, Thomas Parr:
Sophisticated Inference. Neural Comput. 33(3): 713-763 (2021) - [c15]Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba:
Mastering Atari with Discrete World Models. ICLR 2021 - [c14]Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti:
Latent Skill Planning for Exploration and Transfer. ICLR 2021 - [c13]Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine:
Information is Power: Intrinsic Control via Information Capture. NeurIPS 2021: 10745-10758 - [c12]Russell Mendonca, Oleh Rybkin, Kostas Daniilidis, Danijar Hafner, Deepak Pathak:
Discovering and Achieving Goals via World Models. NeurIPS 2021: 24379-24391 - [c11]Vaibhav Saxena, Jimmy Ba, Danijar Hafner:
Clockwork Variational Autoencoders. NeurIPS 2021: 29246-29257 - [i22]Vaibhav Saxena, Jimmy Ba, Danijar Hafner:
Clockwork Variational Autoencoders. CoRR abs/2102.09532 (2021) - [i21]Danijar Hafner:
Benchmarking the Spectrum of Agent Capabilities. CoRR abs/2109.06780 (2021) - [i20]Russell Mendonca, Oleh Rybkin, Kostas Daniilidis, Danijar Hafner, Deepak Pathak:
Discovering and Achieving Goals via World Models. CoRR abs/2110.09514 (2021) - [i19]Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D. Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine:
Information is Power: Intrinsic Control via Information Capture. CoRR abs/2112.03899 (2021) - 2020
- [c10]Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi:
Dream to Control: Learning Behaviors by Latent Imagination. ICLR 2020 - [c9]Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak:
Planning to Explore via Self-Supervised World Models. ICML 2020: 8583-8592 - [i18]Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak:
Planning to Explore via Self-Supervised World Models. CoRR abs/2005.05960 (2020) - [i17]Karl J. Friston, Lancelot Da Costa, Danijar Hafner, Casper Hesp, Thomas Parr:
Sophisticated Inference. CoRR abs/2006.04120 (2020) - [i16]Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl J. Friston, Nicolas Heess:
Action and Perception as Divergence Minimization. CoRR abs/2009.01791 (2020) - [i15]Danijar Hafner, Timothy P. Lillicrap, Mohammad Norouzi, Jimmy Ba:
Mastering Atari with Discrete World Models. CoRR abs/2010.02193 (2020) - [i14]Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti:
Skill Transfer via Partially Amortized Hierarchical Planning. CoRR abs/2011.13897 (2020) - [i13]Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan:
Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning. CoRR abs/2012.04603 (2020) - [i12]Brendon Matusch, Jimmy Ba, Danijar Hafner:
Evaluating Agents without Rewards. CoRR abs/2012.11538 (2020)
2010 – 2019
- 2019
- [j1]Tobias Friedrich, Martin S. Krejca, Ralf Rothenberger, Tobias Arndt, Danijar Hafner, Thomas Kellermeier, Simon Krogmann, Armin Razmjou:
Routing for on-street parking search using probabilistic data. AI Commun. 32(2): 113-124 (2019) - [c8]Thomas Parr, Danijar Hafner, Karl J. Friston:
Disorders of Artificial Awareness. AAAI Spring Symposium: Towards Conscious AI Systems 2019 - [c7]Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson:
Learning Latent Dynamics for Planning from Pixels. ICML 2019: 2555-2565 - [c6]Dustin Tran, Mike Dusenberry, Mark van der Wilk, Danijar Hafner:
Bayesian Layers: A Module for Neural Network Uncertainty. NeurIPS 2019: 14633-14645 - [c5]Danijar Hafner, Dustin Tran, Timothy P. Lillicrap, Alex Irpan, James Davidson:
Noise Contrastive Priors for Functional Uncertainty. UAI 2019: 905-914 - [i11]Danijar Hafner, Timothy P. Lillicrap, Jimmy Ba, Mohammad Norouzi:
Dream to Control: Learning Behaviors by Latent Imagination. CoRR abs/1912.01603 (2019) - 2018
- [c4]Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee:
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion. NeurIPS 2018: 8234-8244 - [c3]Jie Tan, Tingnan Zhang, Erwin Coumans, Atil Iscen, Yunfei Bai, Danijar Hafner, Steven Bohez, Vincent Vanhoucke:
Sim-to-Real: Learning Agile Locomotion For Quadruped Robots. Robotics: Science and Systems 2018 - [i10]Jie Tan, Tingnan Zhang, Erwin Coumans, Atil Iscen, Yunfei Bai, Danijar Hafner, Steven Bohez, Vincent Vanhoucke:
Sim-to-Real: Learning Agile Locomotion For Quadruped Robots. CoRR abs/1804.10332 (2018) - [i9]Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee:
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion. CoRR abs/1807.01675 (2018) - [i8]Danijar Hafner, Dustin Tran, Alex Irpan, Timothy P. Lillicrap, James Davidson:
Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors. CoRR abs/1807.09289 (2018) - [i7]Danijar Hafner, Timothy P. Lillicrap, Ian Fischer, Ruben Villegas, David Ha, Honglak Lee, James Davidson:
Learning Latent Dynamics for Planning from Pixels. CoRR abs/1811.04551 (2018) - [i6]Alexander Pashevich, Danijar Hafner, James Davidson, Rahul Sukthankar, Cordelia Schmid:
Modulated Policy Hierarchies. CoRR abs/1812.00025 (2018) - [i5]Dustin Tran, Michael W. Dusenberry, Mark van der Wilk, Danijar Hafner:
Bayesian Layers: A Module for Neural Network Uncertainty. CoRR abs/1812.03973 (2018) - 2017
- [c2]Danijar Hafner, Alexander Irpan, James Davidson, Nicolas Heess:
Learning Hierarchical Information Flow with Recurrent Neural Modules. NIPS 2017: 6724-6733 - [i4]Danijar Hafner, Alex Irpan, James Davidson, Nicolas Heess:
Learning Hierarchical Information Flow with Recurrent Neural Modules. CoRR abs/1706.05744 (2017) - [i3]Danijar Hafner, James Davidson, Vincent Vanhoucke:
TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow. CoRR abs/1709.02878 (2017) - [i2]Danijar Hafner, Alexander Immer, Willi Raschkowski, Fabian Windheuser:
Generative Interest Estimation for Document Recommendations. CoRR abs/1711.10327 (2017) - 2016
- [c1]Tobias Arndt, Danijar Hafner, Thomas Kellermeier, Simon Krogmann, Armin Razmjou, Martin S. Krejca, Ralf Rothenberger, Tobias Friedrich:
Probabilistic Routing for On-Street Parking Search. ESA 2016: 6:1-6:13 - [i1]Danijar Hafner:
Deep Reinforcement Learning From Raw Pixels in Doom. CoRR abs/1610.02164 (2016)
Coauthor Index
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last updated on 2024-10-07 22:24 CEST by the dblp team
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