Jost Tobias Springenberg

96 papers A* 17A 3Misc 5Journal 53Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	MEM: Multi-Scale Embodied Memory for Vision Language Action Models. CoRR Marcel Torne, Karl Pertsch, Homer Walke, Kyle Vedder, Suraj Nair, Brian Ichter, Allen Z. Ren, Haohuan Wang, Jiaming Tang, Kyle Stachowicz, Karan Dhabalia, Michael Equi, Quan Vuong, Jost Tobias Springenberg, Sergey Levine, Chelsea Finn, Danny Driess
2025	J	`jnl`	Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better. CoRR Danny Driess, Jost Tobias Springenberg, Brian Ichter, Lili Yu, Adrian Li-Bell, Karl Pertsch, Allen Z. Ren, Homer Walke, Quan Vuong, Lucy Xiaoyang Shi, Sergey Levine
2025	A*	`conf`	Learning from negative feedback, or positive feedback or both. ICLR Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Michael Bloesch, Rishabh Joshi, Thomas Lampe, Junhyuk Oh, Nicolas Heess, Jonas Buchli, Martin A. Riedmiller
2025	J	`jnl`	Supervised Fine Tuning on Curated Data is Reinforcement Learning (and can be improved). CoRR Chongli Qin, Jost Tobias Springenberg
2025	J	`jnl`	Value from Observations: Towards Large-Scale Imitation Learning via Self-Improvement. CoRR Michael Bloesch, Markus Wulfmeier, Philemon Brakel, Todor Davchev, Martina Zambelli, Jost Tobias Springenberg, Abbas Abdolmaleki, William F. Whitney, Nicolas Heess, Roland Hafner, Martin A. Riedmiller
2025	J	`jnl`	π CoRR Physical Intelligence, Kevin Black, Noah Brown, James Darpinian, Karan Dhabalia, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Manuel Y. Galliker, Dibya Ghosh, Lachy Groom, Karol Hausman, Brian Ichter, Szymon Jakubczak, Tim Jones, Liyiming Ke, Devin LeBlanc, Sergey Levine, Adrian Li-Bell, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Allen Z. Ren, Lucy Xiaoyang Shi, Laura Smith, Jost Tobias Springenberg, Kyle Stachowicz, James Tanner, Quan Vuong, Homer Walke, Anna Walling, Haohuan Wang, Lili Yu, Ury Zhilinsky
2025	J	`jnl`	π CoRR Physical Intelligence, Ali Amin, Raichelle Aniceto, Ashwin Balakrishna, Kevin Black, Ken Conley, Grace Connors, James Darpinian, Karan Dhabalia, Jared DiCarlo, Danny Driess, Michael Equi, Adnan Esmail, Yunhao Fang, Chelsea Finn, Catherine Glossop, Thomas Godden, Ivan Goryachev, Lachy Groom, Hunter Hancock, Karol Hausman, Gashon Hussein, Brian Ichter, Szymon Jakubczak, Rowan Jen, Tim Jones, Ben Katz, Liyiming Ke, Chandra Kuchi, Marinda Lamb, Devin LeBlanc, Sergey Levine, Adrian Li-Bell, Yao Lu, Vishnu Mano, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Allen Z. Ren, Charvi Sharma, Lucy Xiaoyang Shi, Laura Smith, Jost Tobias Springenberg, Kyle Stachowicz, Will Stoeckle, Alex Swerdlow, James Tanner, Marcel Torne, Quan Vuong, Anna Walling, Haohuan Wang, Blake Williams, Sukwon Yoo, Lili Yu, Ury Zhilinsky, Zhiyuan Zhou
2024	J	`jnl`	GATS: Gather-Attend-Scatter. CoRR Konrad Zolna, Serkan Cabi, Yutian Chen, Eric Lau, Claudio Fantacci, Jurgis Pasukonis, Jost Tobias Springenberg, Sergio Gomez Colmenarejo
2024	J	`jnl`	Game On: Towards Language Models as RL Experimenters. CoRR Jingwei Zhang, Thomas Lampe, Abbas Abdolmaleki, Jost Tobias Springenberg, Martin A. Riedmiller
2024	A*	`conf`	Imitating Language via Scalable Inverse Reinforcement Learning. NeurIPS Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller
2024	J	`jnl`	Imitating Language via Scalable Inverse Reinforcement Learning. CoRR Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Maria Elisabeth Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller
2024	A*	`conf`	Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. ICRA Thomas Lampe, Abbas Abdolmaleki, Sarah Bechtle, Sandy H. Huang, Jost Tobias Springenberg, Michael Bloesch, Oliver Groth, Roland Hafner, Tim Hertweck, Michael Neunert, Markus Wulfmeier, Jingwei Zhang, Francesco Nori, Nicolas Heess, Martin A. Riedmiller
2024	A*	`conf`	Offline Actor-Critic Reinforcement Learning Scales to Large Models. ICML Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang, Oliver Groth, Michael Bloesch, Thomas Lampe, Philemon Brakel, Sarah Bechtle, Steven Kapturowski, Roland Hafner, Nicolas Heess, Martin A. Riedmiller
2024	J	`jnl`	Offline Actor-Critic Reinforcement Learning Scales to Large Models. CoRR Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang, Oliver Groth, Michael Bloesch, Thomas Lampe, Philemon Brakel, Sarah Bechtle, Steven Kapturowski, Roland Hafner, Nicolas Heess, Martin A. Riedmiller
2024	J	`jnl`	Preference Optimization as Probabilistic Inference. CoRR Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Rishabh Joshi, Junhyuk Oh, Michael Bloesch, Thomas Lampe, Nicolas Heess, Jonas Buchli, Martin A. Riedmiller
2024	J	`jnl`	RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation. Trans. Mach. Learn. Res. Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Manon Devin, Alex X. Lee, Maria Bauzá Villalonga, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo Fernandes Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess
2023	J	`jnl`	A Generalist Dynamics Model for Control. CoRR Ingmar Schubert, Jingwei Zhang, Jake Bruce, Sarah Bechtle, Emilio Parisotto, Martin A. Riedmiller, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Nicolas Heess
2023	J	`jnl`	Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains. CoRR Jingwei Zhang, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Abbas Abdolmaleki, Dushyant Rao, Nicolas Heess, Martin A. Riedmiller
2023	J	`jnl`	Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. CoRR Thomas Lampe, Abbas Abdolmaleki, Sarah Bechtle, Sandy H. Huang, Jost Tobias Springenberg, Michael Bloesch, Oliver Groth, Roland Hafner, Tim Hertweck, Michael Neunert, Markus Wulfmeier, Jingwei Zhang, Francesco Nori, Nicolas Heess, Martin A. Riedmiller
2023	J	`jnl`	RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation. CoRR Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X. Lee, Maria Bauzá, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo F. Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott E. Reed, Sergio Gómez Colmenarejo, Jon Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, José Enrique Chen, Yusuf Aytar, Dave Barker, Joy Ortiz, Martin A. Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess
2022	J	`jnl`	A Generalist Agent. CoRR Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas
2022	J	`jnl`	A Generalist Agent. Trans. Mach. Learn. Res. Scott E. Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas
2022	A*	`conf`	Evaluating Model-Based Planning and Planner Amortization for Continuous Control. ICLR Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin A. Riedmiller
2022	A	`conf`	How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation. IROS Alex X. Lee, Coline Devin, Jost Tobias Springenberg, Yuxiang Zhou, Thomas Lampe, Abbas Abdolmaleki, Konstantinos Bousmalis
2022	J	`jnl`	How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation. CoRR Alex X. Lee, Coline Devin, Jost Tobias Springenberg, Yuxiang Zhou, Thomas Lampe, Abbas Abdolmaleki, Konstantinos Bousmalis
2022	J	`jnl`	Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach. CoRR Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, Siqi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin A. Riedmiller
2021	Misc	`conf`	Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. CoRL Alex X. Lee, Coline Manon Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, José Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin A. Riedmiller, Raia Hadsell, Francesco Nori
2021	J	`jnl`	Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. CoRR Alex X. Lee, Coline Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, José Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin A. Riedmiller, Raia Hadsell, Francesco Nori
2021	Misc	`conf`	Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRL Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess
2021	J	`jnl`	Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRR Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess
2021	J	`jnl`	Evaluating model-based planning and planner amortization for continuous control. CoRR Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin A. Riedmiller
2021	J	`jnl`	On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. CoRR Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani, Bobak Shahriari, Jost Tobias Springenberg, Shruti Mishra, Dhruva TB, Arunkumar Byravan, Konstantinos Bousmalis, András György, Csaba Szepesvári, Raia Hadsell, Nicolas Heess, Martin A. Riedmiller
2021	J	`jnl`	Rethinking Exploration for Sample-Efficient Policy Learning. CoRR William F. Whitney, Michael Bloesch, Jost Tobias Springenberg, Abbas Abdolmaleki, Martin A. Riedmiller
2020	—	`conf`	Compositional Transfer in Hierarchical Reinforcement Learning. Robotics: Science and Systems Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Noah Y. Siegel, Tim Hertweck, Thomas Lampe, Nicolas Heess, Martin A. Riedmiller
2020	J	`jnl`	Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics. CoRR Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier, Thomas Lampe, Jost Tobias Springenberg, Roland Hafner, Francesco Romano, Jonas Buchli, Nicolas Heess, Martin A. Riedmiller
2020	A*	`conf`	Critic Regularized Regression. NeurIPS Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
2020	J	`jnl`	Critic Regularized Regression. CoRR Ziyu Wang, Alexander Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Josh Merel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
2020	A*	`conf`	Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning. ICLR Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller
2020	J	`jnl`	Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning. CoRR Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller
2020	Misc	`conf`	Learning Dexterous Manipulation from Suboptimal Experts. CoRL Rae Jeong, Jost Tobias Springenberg, Jackie Kay, Daniel Zheng, Alexandre Galashov, Nicolas Heess, Francesco Nori
2020	J	`jnl`	Learning Dexterous Manipulation from Suboptimal Experts. CoRR Rae Jeong, Jost Tobias Springenberg, Jackie Kay, Daniel Zheng, Yuxiang Zhou, Alexandre Galashov, Nicolas Heess, Francesco Nori
2020	J	`jnl`	Local Search for Policy Iteration in Continuous Control. CoRR Jost Tobias Springenberg, Nicolas Heess, Daniel J. Mankowitz, Josh Merel, Arunkumar Byravan, Abbas Abdolmaleki, Jackie Kay, Jonas Degrave, Julian Schrittwieser, Yuval Tassa, Jonas Buchli, Dan Belov, Martin A. Riedmiller
2020	A*	`conf`	Robust Reinforcement Learning for Continuous Control with Model Misspecification. ICLR Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller
2020	J	`jnl`	Simple Sensor Intentions for Exploration. CoRR Tim Hertweck, Martin A. Riedmiller, Michael Bloesch, Jost Tobias Springenberg, Noah Y. Siegel, Markus Wulfmeier, Roland Hafner, Nicolas Heess
2020	A*	`conf`	Training Generative Adversarial Networks by Solving Ordinary Differential Equations. NeurIPS Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andy Brock, Jeff Donahue, Timothy P. Lillicrap, Pushmeet Kohli
2020	J	`jnl`	Training Generative Adversarial Networks by Solving Ordinary Differential Equations. CoRR Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andrew Brock, Jeff Donahue, Timothy P. Lillicrap, Pushmeet Kohli
2020	A*	`conf`	V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. ICLR H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick
2019	—	`ch.`	Auto-sklearn: Efficient and Robust Automated Machine Learning. Automated Machine Learning Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter
2019	Misc	`conf`	Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics. CoRL Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier, Thomas Lampe, Jost Tobias Springenberg, Roland Hafner, Francesco Romano, Jonas Buchli, Nicolas Heess, Martin A. Riedmiller
2019	Misc	`conf`	Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models. CoRL Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
2019	J	`jnl`	Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models. CoRR Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
2019	J	`jnl`	Quinoa: a Q-function You Infer Normalized Over Actions. CoRR Jonas Degrave, Abbas Abdolmaleki, Jost Tobias Springenberg, Nicolas Heess, Martin A. Riedmiller
2019	J	`jnl`	Regularized Hierarchical Policies for Compositional Transfer in Robotics. CoRR Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Tim Hertweck, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
2019	J	`jnl`	Robust Reinforcement Learning for Continuous Control with Model Misspecification. CoRR Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy A. Mann, Todd Hester, Martin A. Riedmiller
2019	J	`jnl`	Self-supervised Learning of Image Embedding for Continuous Control. CoRR Carlos Florensa, Jonas Degrave, Nicolas Heess, Jost Tobias Springenberg, Martin A. Riedmiller
2019	—	`conf`	Simultaneously Learning Vision and Feature-Based Control Policies for Real-World Ball-In-A-Cup. Robotics: Science and Systems Devin Schwab, Jost Tobias Springenberg, Murilo Fernandes Martins, Michael Neunert, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Roland Hafner, Francesco Nori, Martin A. Riedmiller
2019	J	`jnl`	Simultaneously Learning Vision and Feature-based Control Policies for Real-world Ball-in-a-Cup. CoRR Devin Schwab, Jost Tobias Springenberg, Murilo F. Martins, Thomas Lampe, Michael Neunert, Abbas Abdolmaleki, Tim Hertweck, Roland Hafner, Francesco Nori, Martin A. Riedmiller
2019	—	`ch.`	Towards Automatically-Tuned Deep Neural Networks. Automated Machine Learning Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Matthias Urban, Michael Burkart, Maximilian Dippel, Marius Lindauer, Frank Hutter
2019	J	`jnl`	V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. CoRR H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick
2018	A*	`conf`	Graph Networks as Learnable Physics Engines for Inference and Control. ICML Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin A. Riedmiller, Raia Hadsell, Peter W. Battaglia
2018	J	`jnl`	Graph networks as learnable physics engines for inference and control. CoRR Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin A. Riedmiller, Raia Hadsell, Peter W. Battaglia
2018	—	`conf`	Learning an Embedding Space for Transferable Robot Skills. ICLR (Poster) Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, Nicolas Heess, Martin A. Riedmiller
2018	J	`jnl`	Learning by Playing - Solving Sparse Reward Tasks from Scratch. CoRR Martin A. Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Volodymyr Mnih, Nicolas Heess, Jost Tobias Springenberg
2018	A*	`conf`	Learning by Playing Solving Sparse Reward Tasks from Scratch. ICML Martin A. Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Vlad Mnih, Nicolas Heess, Jost Tobias Springenberg
2018	—	`conf`	Maximum a Posteriori Policy Optimisation. ICLR (Poster) Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller
2018	J	`jnl`	Maximum a Posteriori Policy Optimisation. CoRR Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller
2018	J	`jnl`	Relative Entropy Regularized Policy Iteration. CoRR Abbas Abdolmaleki, Jost Tobias Springenberg, Jonas Degrave, Steven Bohez, Yuval Tassa, Dan Belov, Nicolas Heess, Martin A. Riedmiller
2017	J	`jnl`	Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG. CoRR Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas Dominique Josef Fiederer, Martin Glasstetter, Katharina Eggensperger, Michael Tangermann, Frank Hutter, Wolfram Burgard, Tonio Ball
2017	A	`conf`	Deep reinforcement learning with successor features for navigation across similar environments. IROS Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker, Wolfram Burgard
2017	—	`conf`	Learning Curve Prediction with Bayesian Neural Networks. ICLR (Poster) Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter
2017	J	`jnl`	Learning to Generate Chairs, Tables and Cars with Convolutional Networks. IEEE Trans. Pattern Anal. Mach. Intell. Alexey Dosovitskiy, Jost Tobias Springenberg, Maxim Tatarchenko, Thomas Brox
2016	J	`jnl`	Asynchronous Stochastic Gradient MCMC with Elastic Coupling. CoRR Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter
2016	—	`conf`	Bayesian Optimization with Robust Bayesian Neural Networks. NIPS Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter
2016	J	`jnl`	Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments. CoRR Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker, Wolfram Burgard
2016	J	`jnl`	Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox
2016	—	`conf`	Towards Automatically-Tuned Neural Networks. AutoML@ICML Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Frank Hutter
2016	A*	`conf`	Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks. ICLR (Poster) Jost Tobias Springenberg
2015	J	`jnl`	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. Wendelin Böhmer, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller, Klaus Obermayer
2015	—	`conf`	Efficient and Robust Automated Machine Learning. NIPS Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter
2015	—	`conf`	Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images. NIPS Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller
2015	J	`jnl`	Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images. CoRR Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller
2015	A*	`conf`	Initializing Bayesian Hyperparameter Optimization via Meta-Learning. AAAI Matthias Feurer, Jost Tobias Springenberg, Frank Hutter
2015	A*	`conf`	Learning to generate chairs with convolutional neural networks. CVPR Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox
2015	J	`jnl`	Multimodal Deep Learning for Robust RGB-D Object Recognition. CoRR Andreas Eitel, Jost Tobias Springenberg, Luciano Spinello, Martin A. Riedmiller, Wolfram Burgard
2015	A	`conf`	Multimodal deep learning for robust RGB-D object recognition. IROS Andreas Eitel, Jost Tobias Springenberg, Luciano Spinello, Martin A. Riedmiller, Wolfram Burgard
2015	A*	`conf`	Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves. IJCAI Tobias Domhan, Jost Tobias Springenberg, Frank Hutter
2015	—	`conf`	Striving for Simplicity: The All Convolutional Net. ICLR (Workshop) Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, Martin A. Riedmiller
2014	—	`conf`	Approximate real-time optimal control based on sparse Gaussian process models. ADPRL Joschka Boedecker, Jost Tobias Springenberg, Jan Wülfing, Martin A. Riedmiller
2014	—	`conf`	Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. NIPS Alexey Dosovitskiy, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox
2014	J	`jnl`	Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. CoRR Alexey Dosovitskiy, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox
2014	—	`conf`	Improving Deep Neural Networks with Probabilistic Maxout Units. ICLR (Workshop Poster) Jost Tobias Springenberg, Martin A. Riedmiller
2014	J	`jnl`	Learning to Generate Chairs with Convolutional Neural Networks. CoRR Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox
2014	—	`conf`	Unsupervised feature learning by augmenting single images. ICLR (Workshop Poster) Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox
2014	—	`conf`	Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters. MetaSel@ECAI Matthias Feurer, Jost Tobias Springenberg, Frank Hutter
2012	A*	`conf`	A learned feature descriptor for object recognition in RGB-D data. ICRA Manuel Blum, Jost Tobias Springenberg, Jan Wülfing, Martin A. Riedmiller
2012	—	`conf`	Learning Temporal Coherent Features through Life-Time Sparsity. ICONIP (1) Jost Tobias Springenberg, Martin A. Riedmiller