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ORCIDJost Tobias Springenberg
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- affiliation: University of Freiburg, Machine Learning Lab
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2020 – today
- 2024
[j5]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:
RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation. Trans. Mach. Learn. Res. 2024 (2024)- [c39]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:
Offline Actor-Critic Reinforcement Learning Scales to Large Models. ICML 2024 - [c38]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:
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. ICRA 2024: 7772-7779 - [i42]Konrad Zolna, Serkan Cabi, Yutian Chen, Eric Lau, Claudio Fantacci, Jurgis Pasukonis, Jost Tobias Springenberg, Sergio Gomez Colmenarejo:
GATS: Gather-Attend-Scatter. CoRR abs/2401.08525 (2024) - [i41]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:
Offline Actor-Critic Reinforcement Learning Scales to Large Models. CoRR abs/2402.05546 (2024) - [i40]Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jorg 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:
Imitating Language via Scalable Inverse Reinforcement Learning. CoRR abs/2409.01369 (2024) - [i39]Jingwei Zhang, Thomas Lampe, Abbas Abdolmaleki, Jost Tobias Springenberg, Martin A. Riedmiller:
Game On: Towards Language Models as RL Experimenters. CoRR abs/2409.03402 (2024) - [i38]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:
Preference Optimization as Probabilistic Inference. CoRR abs/2410.04166 (2024) - 2023
- [i37]Jingwei Zhang, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Abbas Abdolmaleki, Dushyant Rao, Nicolas Heess, Martin A. Riedmiller:
Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains. CoRR abs/2302.12617 (2023) - [i36]Ingmar Schubert, Jingwei Zhang, Jake Bruce, Sarah Bechtle, Emilio Parisotto, Martin A. Riedmiller, Jost Tobias Springenberg, Arunkumar Byravan, Leonard Hasenclever, Nicolas Heess:
A Generalist Dynamics Model for Control. CoRR abs/2305.10912 (2023) - [i35]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:
RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation. CoRR abs/2306.11706 (2023) - [i34]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:
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. CoRR abs/2312.11374 (2023) - 2022
- [j4]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:
A Generalist Agent. Trans. Mach. Learn. Res. 2022 (2022) - [c37]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:
Evaluating Model-Based Planning and Planner Amortization for Continuous Control. ICLR 2022 - [c36]Alex X. Lee, Coline Devin, Jost Tobias Springenberg, Yuxiang Zhou, Thomas Lampe, Abbas Abdolmaleki, Konstantinos Bousmalis:
How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation. IROS 2022: 2468-2475 - [i33]Bobak Shahriari, Abbas Abdolmaleki, Arunkumar Byravan, Abe Friesen, Siqi Liu, Jost Tobias Springenberg, Nicolas Heess, Matt Hoffman, Martin A. Riedmiller:
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach. CoRR abs/2204.10256 (2022) - [i32]Alex X. Lee, Coline Devin, Jost Tobias Springenberg, Yuxiang Zhou, Thomas Lampe, Abbas Abdolmaleki, Konstantinos Bousmalis:
How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation. CoRR abs/2205.03353 (2022) - [i31]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:
A Generalist Agent. CoRR abs/2205.06175 (2022) - 2021
- [c35]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:
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. CoRL 2021: 1089-1131 - [c34]Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess:
Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRL 2021: 1736-1744 - [i30]William F. Whitney, Michael Bloesch, Jost Tobias Springenberg, Abbas Abdolmaleki, Martin A. Riedmiller:
Rethinking Exploration for Sample-Efficient Policy Learning. CoRR abs/2101.09458 (2021) - [i29]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:
On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. CoRR abs/2106.08199 (2021) - [i28]Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess:
Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRR abs/2108.10273 (2021) - [i27]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:
Evaluating model-based planning and planner amortization for continuous control. CoRR abs/2110.03363 (2021) - [i26]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:
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes. CoRR abs/2110.06192 (2021) - 2020
- [c33]Rae Jeong, Jost Tobias Springenberg, Jackie Kay, Daniel Zheng, Alexandre Galashov, Nicolas Heess, Francesco Nori:
Learning Dexterous Manipulation from Suboptimal Experts. CoRL 2020: 915-934 - [c32]Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller:
Robust Reinforcement Learning for Continuous Control with Model Misspecification. ICLR 2020 - [c31]Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller:
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning. ICLR 2020 - [c30]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:
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. ICLR 2020 - [c29]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:
Critic Regularized Regression. NeurIPS 2020 - [c28]Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andy Brock, Jeff Donahue, Timothy P. Lillicrap, Pushmeet Kohli:
Training Generative Adversarial Networks by Solving Ordinary Differential Equations. NeurIPS 2020 - [c27]Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Noah Y. Siegel, Tim Hertweck, Thomas Lampe, Nicolas Heess, Martin A. Riedmiller:
Compositional Transfer in Hierarchical Reinforcement Learning. Robotics: Science and Systems 2020 - [i25]Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier, Thomas Lampe, Jost Tobias Springenberg, Roland Hafner, Francesco Romano, Jonas Buchli, Nicolas Heess, Martin A. Riedmiller:
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics. CoRR abs/2001.00449 (2020) - [i24]Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller:
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning. CoRR abs/2002.08396 (2020) - [i23]Tim Hertweck, Martin A. Riedmiller, Michael Bloesch, Jost Tobias Springenberg, Noah Y. Siegel, Markus Wulfmeier, Roland Hafner, Nicolas Heess:
Simple Sensor Intentions for Exploration. CoRR abs/2005.07541 (2020) - [i22]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:
Critic Regularized Regression. CoRR abs/2006.15134 (2020) - [i21]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:
Local Search for Policy Iteration in Continuous Control. CoRR abs/2010.05545 (2020) - [i20]Rae Jeong, Jost Tobias Springenberg, Jackie Kay, Daniel Zheng, Yuxiang Zhou, Alexandre Galashov, Nicolas Heess, Francesco Nori:
Learning Dexterous Manipulation from Suboptimal Experts. CoRR abs/2010.08587 (2020) - [i19]Chongli Qin, Yan Wu, Jost Tobias Springenberg, Andrew Brock, Jeff Donahue, Timothy P. Lillicrap, Pushmeet Kohli:
Training Generative Adversarial Networks by Solving Ordinary Differential Equations. CoRR abs/2010.15040 (2020)
2010 – 2019
- 2019
- [c26]Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller:
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models. CoRL 2019: 566-589 - [c25]Michael Neunert, Abbas Abdolmaleki, Markus Wulfmeier, Thomas Lampe, Jost Tobias Springenberg, Roland Hafner, Francesco Romano, Jonas Buchli, Nicolas Heess, Martin A. Riedmiller:
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics. CoRL 2019: 735-751 - [c24]Devin Schwab, Jost Tobias Springenberg, Murilo Fernandes Martins, Michael Neunert, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Roland Hafner, Francesco Nori, Martin A. Riedmiller:
Simultaneously Learning Vision and Feature-Based Control Policies for Real-World Ball-In-A-Cup. Robotics: Science and Systems 2019 - [p2]Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter:
Auto-sklearn: Efficient and Robust Automated Machine Learning. Automated Machine Learning 2019: 113-134 - [p1]Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Matthias Urban, Michael Burkart, Maximilian Dippel, Marius Lindauer, Frank Hutter:
Towards Automatically-Tuned Deep Neural Networks. Automated Machine Learning 2019: 135-149 - [i18]Carlos Florensa, Jonas Degrave, Nicolas Heess, Jost Tobias Springenberg, Martin A. Riedmiller:
Self-supervised Learning of Image Embedding for Continuous Control. CoRR abs/1901.00943 (2019) - [i17]Devin Schwab, Jost Tobias Springenberg, Murilo F. Martins, Thomas Lampe, Michael Neunert, Abbas Abdolmaleki, Tim Hertweck, Roland Hafner, Francesco Nori, Martin A. Riedmiller:
Simultaneously Learning Vision and Feature-based Control Policies for Real-world Ball-in-a-Cup. CoRR abs/1902.04706 (2019) - [i16]Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy A. Mann, Todd Hester, Martin A. Riedmiller:
Robust Reinforcement Learning for Continuous Control with Model Misspecification. CoRR abs/1906.07516 (2019) - [i15]Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Tim Hertweck, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller:
Regularized Hierarchical Policies for Compositional Transfer in Robotics. CoRR abs/1906.11228 (2019) - [i14]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:
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. CoRR abs/1909.12238 (2019) - [i13]Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller:
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models. CoRR abs/1910.04142 (2019) - [i12]Jonas Degrave, Abbas Abdolmaleki, Jost Tobias Springenberg, Nicolas Heess, Martin A. Riedmiller:
Quinoa: a Q-function You Infer Normalized Over Actions. CoRR abs/1911.01831 (2019) - 2018
- [c23]Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller:
Maximum a Posteriori Policy Optimisation. ICLR (Poster) 2018 - [c22]Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, Nicolas Heess, Martin A. Riedmiller:
Learning an Embedding Space for Transferable Robot Skills. ICLR (Poster) 2018 - [c21]Martin A. Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Vlad Mnih, Nicolas Heess, Jost Tobias Springenberg:
Learning by Playing Solving Sparse Reward Tasks from Scratch. ICML 2018: 4341-4350 - [c20]Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin A. Riedmiller, Raia Hadsell, Peter W. Battaglia:
Graph Networks as Learnable Physics Engines for Inference and Control. ICML 2018: 4467-4476 - [i11]Martin A. Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Van de Wiele, Volodymyr Mnih, Nicolas Heess, Jost Tobias Springenberg:
Learning by Playing - Solving Sparse Reward Tasks from Scratch. CoRR abs/1802.10567 (2018) - [i10]Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin A. Riedmiller, Raia Hadsell, Peter W. Battaglia:
Graph networks as learnable physics engines for inference and control. CoRR abs/1806.01242 (2018) - [i9]Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller:
Maximum a Posteriori Policy Optimisation. CoRR abs/1806.06920 (2018) - [i8]Abbas Abdolmaleki, Jost Tobias Springenberg, Jonas Degrave, Steven Bohez, Yuval Tassa, Dan Belov, Nicolas Heess, Martin A. Riedmiller:
Relative Entropy Regularized Policy Iteration. CoRR abs/1812.02256 (2018) - 2017
- [j3]Alexey Dosovitskiy, Jost Tobias Springenberg, Maxim Tatarchenko, Thomas Brox:
Learning to Generate Chairs, Tables and Cars with Convolutional Networks. IEEE Trans. Pattern Anal. Mach. Intell. 39(4): 692-705 (2017) - [c19]Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter:
Learning Curve Prediction with Bayesian Neural Networks. ICLR (Poster) 2017 - [c18]Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker, Wolfram Burgard:
Deep reinforcement learning with successor features for navigation across similar environments. IROS 2017: 2371-2378 - [i7]Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas Dominique Josef Fiederer, Martin Glasstetter, Katharina Eggensperger, Michael Tangermann, Frank Hutter, Wolfram Burgard, Tonio Ball:
Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG. CoRR abs/1703.05051 (2017) - 2016
- [j2]Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox:
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 38(9): 1734-1747 (2016) - [c17]Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Frank Hutter:
Towards Automatically-Tuned Neural Networks. AutoML@ICML 2016: 58-65 - [c16]Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter:
Bayesian Optimization with Robust Bayesian Neural Networks. NIPS 2016: 4134-4142 - [c15]Jost Tobias Springenberg:
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks. ICLR (Poster) 2016 - [i6]Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter:
Asynchronous Stochastic Gradient MCMC with Elastic Coupling. CoRR abs/1612.00767 (2016) - [i5]Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker, Wolfram Burgard:
Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments. CoRR abs/1612.05533 (2016) - 2015
- [j1]Wendelin Böhmer, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller, Klaus Obermayer:
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. 29(4): 353-362 (2015) - [c14]Matthias Feurer, Jost Tobias Springenberg, Frank Hutter:
Initializing Bayesian Hyperparameter Optimization via Meta-Learning. AAAI 2015: 1128-1135 - [c13]Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox:
Learning to generate chairs with convolutional neural networks. CVPR 2015: 1538-1546 - [c12]Tobias Domhan, Jost Tobias Springenberg, Frank Hutter:
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves. IJCAI 2015: 3460-3468 - [c11]Andreas Eitel, Jost Tobias Springenberg, Luciano Spinello, Martin A. Riedmiller, Wolfram Burgard:
Multimodal deep learning for robust RGB-D object recognition. IROS 2015: 681-687 - [c10]Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller:
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images. NIPS 2015: 2746-2754 - [c9]Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter:
Efficient and Robust Automated Machine Learning. NIPS 2015: 2962-2970 - [c8]Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, Martin A. Riedmiller:
Striving for Simplicity: The All Convolutional Net. ICLR (Workshop) 2015 - [i4]Manuel Watter, Jost Tobias Springenberg, Joschka Boedecker, Martin A. Riedmiller:
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images. CoRR abs/1506.07365 (2015) - [i3]Andreas Eitel, Jost Tobias Springenberg, Luciano Spinello, Martin A. Riedmiller, Wolfram Burgard:
Multimodal Deep Learning for Robust RGB-D Object Recognition. CoRR abs/1507.06821 (2015) - 2014
- [c7]Joschka Boedecker, Jost Tobias Springenberg, Jan Wülfing, Martin A. Riedmiller:
Approximate real-time optimal control based on sparse Gaussian process models. ADPRL 2014: 1-8 - [c6]Matthias Feurer, Jost Tobias Springenberg, Frank Hutter:
Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters. MetaSel@ECAI 2014: 3-10 - [c5]Alexey Dosovitskiy, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox:
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. NIPS 2014: 766-774 - [c4]Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox:
Unsupervised feature learning by augmenting single images. ICLR (Workshop Poster) 2014 - [c3]Jost Tobias Springenberg, Martin A. Riedmiller:
Improving Deep Neural Networks with Probabilistic Maxout Units. ICLR (Workshop Poster) 2014 - [i2]Alexey Dosovitskiy, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox:
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. CoRR abs/1406.6909 (2014) - [i1]Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox:
Learning to Generate Chairs with Convolutional Neural Networks. CoRR abs/1411.5928 (2014) - 2012
- [c2]Jost Tobias Springenberg, Martin A. Riedmiller:
Learning Temporal Coherent Features through Life-Time Sparsity. ICONIP (1) 2012: 347-356 - [c1]Manuel Blum, Jost Tobias Springenberg, Jan Wülfing, Martin A. Riedmiller:
A learned feature descriptor for object recognition in RGB-D data. ICRA 2012: 1298-1303
Coauthor Index
[j5] [c39] [c38] [i41] [i40] [i39] [i38] [i37] [i36] [i35] [i34] [c37] [i33] [c35] [c34] [i30] [i29] [i28] [i27] [i26] [c32] [c31] [c30] [c27] [i25] [i24] [i23] [i21] [c26] [c25] [c24] [i18] [i17] [i16] [i15] [i14] [i13] [i12] [c23] [c22] [c21] [c20] [i11] [i10] [i9] [i8] [j2] [j1] [c11] [c10] [c8] [i4] [i3] [c7] [c5] [c3] [i2] [c2] [c1]
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last updated on 2025-01-09 12:56 CET by the dblp team
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