Jost Tobias Springenberg
Affiliations:- University of Freiburg, Machine Learning Lab
According to our database1,
Jost Tobias Springenberg
authored at least 68 papers
between 2012 and 2024.
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Bibliography
2024
Trans. Mach. Learn. Res., 2024
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
CoRR, 2023
2022
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach.
CoRR, 2022
How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
CoRR, 2021
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021
2020
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning.
CoRR, 2020
Proceedings of the Robotics: Science and Systems XVI, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control.
Proceedings of the 8th International Conference on Learning Representations, 2020
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 4th Conference on Robot Learning, 2020
2019
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models.
CoRR, 2019
CoRR, 2019
Simultaneously Learning Vision and Feature-Based Control Policies for Real-World Ball-In-A-Cup.
Proceedings of the Robotics: Science and Systems XV, 2019
Proceedings of the 3rd Annual Conference on Robot Learning, 2019
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019
2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
2017
IEEE Trans. Pattern Anal. Mach. Intell., 2017
Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG.
CoRR, 2017
Deep reinforcement learning with successor features for navigation across similar environments.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017
Proceedings of the 5th International Conference on Learning Representations, 2017
2016
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2016
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks.
Proceedings of the 4th International Conference on Learning Representations, 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016
2015
Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations.
Künstliche Intell., 2015
Proceedings of the 3rd International Conference on Learning Representations, 2015
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2014
Proceedings of the 2nd International Conference on Learning Representations, 2014
Proceedings of the 2nd International Conference on Learning Representations, 2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014
Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014
2012
Proceedings of the IEEE International Conference on Robotics and Automation, 2012
Proceedings of the Neural Information Processing - 19th International Conference, 2012