Jost Tobias Springenberg

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 63

Top Topics

Reinforcement Learning

Top Venues

Publications

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)
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)
Konrad Zolna, Serkan Cabi, Yutian Chen, Eric Lau, Claudio Fantacci, Jurgis Pasukonis, Jost Tobias Springenberg, Sergio Gomez Colmenarejo
GATS: Gather-Attend-Scatter. CoRR (2024)
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 (2024)
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, Jose 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 (2023)
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 (2023)
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 (2023)
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 (2023)
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 (2022)
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)
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)
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)
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 (2022)
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 (2022)
Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess
Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRL (2021)
William F. Whitney, Michael Bloesch, Jost Tobias Springenberg, Abbas Abdolmaleki, Martin A. Riedmiller
Rethinking Exploration for Sample-Efficient Policy Learning. CoRR (2021)
Martin A. Riedmiller, Jost Tobias Springenberg, Roland Hafner, Nicolas Heess
Collect & Infer - a fresh look at data-efficient Reinforcement Learning. CoRR (2021)
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 (2021)
Alex X. Lee, Coline Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, Jose 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 (2021)
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 (2021)
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, Jose 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)
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)
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)
Rae Jeong, Jost Tobias Springenberg, Jackie Kay, Daniel Zheng, Yuxiang Zhou, Alexandre Galashov, Nicolas Heess, Francesco Nori
Learning Dexterous Manipulation from Suboptimal Experts. CoRR (2020)
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 (2020)
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)
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 (2020)
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)
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 (2020)
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)
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 (2020)
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 (2020)
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 (2020)
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)
Rae Jeong, Jost Tobias Springenberg, Jackie Kay, Daniel Zheng, Alexandre Galashov, Nicolas Heess, Francesco Nori
Learning Dexterous Manipulation from Suboptimal Experts. CoRL (2020)
Jonas Degrave, Abbas Abdolmaleki, Jost Tobias Springenberg, Nicolas Heess, Martin A. Riedmiller
Quinoa: a Q-function You Infer Normalized Over Actions. CoRR (2019)
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 (2019)
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 (2019)
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)
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 (2019)
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)
Carlos Florensa, Jonas Degrave, Nicolas Heess, Jost Tobias Springenberg, Martin A. Riedmiller
Self-supervised Learning of Image Embedding for Continuous Control. CoRR (2019)
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 (2019)
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 (2019)
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)
Abbas Abdolmaleki, Jost Tobias Springenberg, Jonas Degrave, Steven Bohez, Yuval Tassa, Dan Belov, Nicolas Heess, Martin A. Riedmiller
Relative Entropy Regularized Policy Iteration. CoRR (2018)
Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller
Maximum a Posteriori Policy Optimisation. ICLR (Poster) (2018)
Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa, Rémi Munos, Nicolas Heess, Martin A. Riedmiller
Maximum a Posteriori Policy Optimisation. CoRR (2018)
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)
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)
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 (2018)
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 (2018)
Karol Hausman, Jost Tobias Springenberg, Ziyu Wang, Nicolas Heess, Martin A. Riedmiller
Learning an Embedding Space for Transferable Robot Skills. ICLR (Poster) (2018)
Aaron Klein, Stefan Falkner, Jost Tobias Springenberg, Frank Hutter
Learning Curve Prediction with Bayesian Neural Networks. ICLR (Poster) (2017)
Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker, Wolfram Burgard
Deep reinforcement learning with successor features for navigation across similar environments. IROS (2017)
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) (2017)
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 (2017)
Jost Tobias Springenberg
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks. ICLR (Poster) (2016)
Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter
Asynchronous Stochastic Gradient MCMC with Elastic Coupling. CoRR (2016)
Jost Tobias Springenberg, Aaron Klein, Stefan Falkner, Frank Hutter
Bayesian Optimization with Robust Bayesian Neural Networks. NIPS (2016)
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) (2016)
Hector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Frank Hutter
Towards Automatically-Tuned Neural Networks. AutoML@ICML (2016)
Jingwei Zhang, Jost Tobias Springenberg, Joschka Boedecker, Wolfram Burgard
Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments. CoRR (2016)
Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum, Frank Hutter
Efficient and Robust Automated Machine Learning. NIPS (2015)
Tobias Domhan, Jost Tobias Springenberg, Frank Hutter
Speeding Up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves. IJCAI (2015)
Andreas Eitel, Jost Tobias Springenberg, Luciano Spinello, Martin A. Riedmiller, Wolfram Burgard
Multimodal deep learning for robust RGB-D object recognition. IROS (2015)
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)
Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox
Learning to generate chairs with convolutional neural networks. CVPR (2015)
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) (2015)
Matthias Feurer, Jost Tobias Springenberg, Frank Hutter
Initializing Bayesian Hyperparameter Optimization via Meta-Learning. AAAI (2015)
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 (2015)
Andreas Eitel, Jost Tobias Springenberg, Luciano Spinello, Martin A. Riedmiller, Wolfram Burgard
Multimodal Deep Learning for Robust RGB-D Object Recognition. CoRR (2015)
Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, Martin A. Riedmiller
Striving for Simplicity: The All Convolutional Net. ICLR (Workshop) (2015)
Jost Tobias Springenberg, Martin A. Riedmiller
Improving Deep Neural Networks with Probabilistic Maxout Units. ICLR (Workshop Poster) (2014)
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. CoRR (2014)
Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox
Learning to Generate Chairs with Convolutional Neural Networks. CoRR (2014)
Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox
Unsupervised feature learning by augmenting single images. ICLR (Workshop Poster) (2014)
Joschka Boedecker, Jost Tobias Springenberg, Jan Wülfing, Martin A. Riedmiller
Approximate real-time optimal control based on sparse Gaussian process models. ADPRL (2014)
Matthias Feurer, Jost Tobias Springenberg, Frank Hutter
Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters. MetaSel@ECAI (2014)
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin A. Riedmiller, Thomas Brox
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. NIPS (2014)
Jost Tobias Springenberg, Martin A. Riedmiller
Learning Temporal Coherent Features through Life-Time Sparsity. ICONIP (1) (2012)
Manuel Blum, Jost Tobias Springenberg, Jan Wülfing, Martin A. Riedmiller
A learned feature descriptor for object recognition in RGB-D data. ICRA (2012)