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
RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation.
Trans. Mach. Learn. Res., 2024

Preference Optimization as Probabilistic Inference.
CoRR, 2024

Game On: Towards Language Models as RL Experimenters.
CoRR, 2024

Imitating Language via Scalable Inverse Reinforcement Learning.
CoRR, 2024

GATS: Gather-Attend-Scatter.
CoRR, 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

Offline Actor-Critic Reinforcement Learning Scales to Large Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation.
CoRR, 2023

A Generalist Dynamics Model for Control.
CoRR, 2023

Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains.
CoRR, 2023

2022
A Generalist Agent.
Trans. Mach. Learn. Res., 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

Evaluating Model-Based Planning and Planner Amortization for Continuous Control.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
On Multi-objective Policy Optimization as a Tool for Reinforcement Learning.
CoRR, 2021

Rethinking Exploration for Sample-Efficient Policy Learning.
CoRR, 2021

Collect & Infer - a fresh look at data-efficient Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021


2020
Learning Dexterous Manipulation from Suboptimal Experts.
CoRR, 2020

Local Search for Policy Iteration in Continuous Control.
CoRR, 2020

Simple Sensor Intentions for Exploration.
CoRR, 2020

Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning.
CoRR, 2020

Compositional Transfer in Hierarchical Reinforcement Learning.
Proceedings of the Robotics: Science and Systems XVI, 2020

Training Generative Adversarial Networks by Solving Ordinary Differential Equations.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Critic Regularized Regression.
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

Robust Reinforcement Learning for Continuous Control with Model Misspecification.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Dexterous Manipulation from Suboptimal Experts.
Proceedings of the 4th Conference on Robot Learning, 2020

2019
Quinoa: a Q-function You Infer Normalized Over Actions.
CoRR, 2019

Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models.
CoRR, 2019

Regularized Hierarchical Policies for Compositional Transfer in Robotics.
CoRR, 2019

Robust Reinforcement Learning for Continuous Control with Model Misspecification.
CoRR, 2019

Self-supervised Learning of Image Embedding for Continuous Control.
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

Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics.
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

Towards Automatically-Tuned Deep Neural Networks.
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Auto-sklearn: Efficient and Robust Automated Machine Learning.
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

2018
Relative Entropy Regularized Policy Iteration.
CoRR, 2018

Graph Networks as Learnable Physics Engines for Inference and Control.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning by Playing Solving Sparse Reward Tasks from Scratch.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning an Embedding Space for Transferable Robot Skills.
Proceedings of the 6th International Conference on Learning Representations, 2018

Maximum a Posteriori Policy Optimisation.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Learning to Generate Chairs, Tables and Cars with Convolutional Networks.
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

Learning Curve Prediction with Bayesian Neural Networks.
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

Asynchronous Stochastic Gradient MCMC with Elastic Coupling.
CoRR, 2016

Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks.
Proceedings of the 4th International Conference on Learning Representations, 2016

Bayesian Optimization with Robust Bayesian Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Towards Automatically-Tuned Neural Networks.
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

Striving for Simplicity: The All Convolutional Net.
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

Efficient and Robust Automated Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Multimodal deep learning for robust RGB-D object recognition.
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

Learning to generate chairs with convolutional neural networks.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

Initializing Bayesian Hyperparameter Optimization via Meta-Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Improving Deep Neural Networks with Probabilistic Maxout Units.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Unsupervised feature learning by augmenting single images.
Proceedings of the 2nd International Conference on Learning Representations, 2014

Discriminative Unsupervised Feature Learning with Convolutional Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters.
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014

Approximate real-time optimal control based on sparse Gaussian process models.
Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

2012
A learned feature descriptor for object recognition in RGB-D data.
Proceedings of the IEEE International Conference on Robotics and Automation, 2012

Learning Temporal Coherent Features through Life-Time Sparsity.
Proceedings of the Neural Information Processing - 19th International Conference, 2012


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