Jost Tobias Springenberg
- Cognitive Neuroscience top 1%
- Neural dynamics and brain function 3
- Human-Computer Interaction top 0.5%
-
- Advanced Neural Network Applications 4
- Advanced Image and Video Retrieval Techniques 4
- Artificial Intelligence top 0.5%
- Reinforcement Learning in Robotics 11
- Machine Learning and Algorithms 6
- Machine Learning and Data Classification 6
- Adversarial Robustness in Machine Learning 5
- Signal Processing top 1%
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- Advanced Multi-Objective Optimization Algorithms 3
- Co-authors
- Frank HutterKatharina EggenspergerThomas BroxAlexey DosovitskiyWolfram BurgardMartin RiedmillerLukas D. J. FiedererMichael Tangermann
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (2 papers)Human Brain Mapping (1 paper)KI - Künstliche Intelligenz (1 paper)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Jost Tobias Springenberg
30 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Cognitive Neuroscience 2.0k
- Human-Computer Interaction 410
- Computer Vision and Pattern Recognition 1.5k
- Artificial Intelligence 2.0k
- Signal Processing 532
Countries citing papers authored by Jost Tobias Springenberg
This map shows the geographic impact of Jost Tobias Springenberg's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jost Tobias Springenberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jost Tobias Springenberg more than expected).
Fields of papers citing papers by Jost Tobias Springenberg
This network shows the impact of papers produced by Jost Tobias Springenberg. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jost Tobias Springenberg. The network helps show where Jost Tobias Springenberg may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jost Tobias Springenberg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2022 | 4 | |
| 3 | Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning | 2020 | 17 |
| 4 | Critic Regularized Regression | 2020 | 1 |
| 5 | V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control | 2020 | 3 |
| 6 | Robust Reinforcement Learning for Continuous Control with Model Misspecification | 2020 | 1 |
| 7 | Learning an Embedding Space for Transferable Robot Skills | 2018 | 66 |
| 8 | Maximum a Posteriori Policy Optimisation | 2018 | 10 |
| 9 | Learning by Playing - Solving Sparse Reward Tasks from Scratch | 2018 | 48 |
| 10 | Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG. | 2017 | 41 |
| 11 | Deep learning with convolutional neural networks for EEG decoding and visualizationbreakdown → | 2017 | 2114 |
| 12 | Learning Curve Prediction with Bayesian Neural Networks | 2017 | 67 |
| 13 | Towards Automatically-Tuned Neural Networks | 2016 | 60 |
| 14 | Bayesian optimization with robust Bayesian neural networks | 2016 | 119 |
| 15 | Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves | 2015 | 200 |
| 16 | Efficient and robust automated machine learningbreakdown → | 2015 | 704 |
| 17 | Embed to control: a locally Linear Latent dynamics model for control from raw images | 2015 | 132 |
| 18 | 2015 | 211 | |
| 19 | Discriminative Unsupervised Feature Learning with Convolutional Neural Networksbreakdown → | 2014 | 289 |
| 20 | Unsupervised feature learning by augmenting single images | 2013 | 3 |
About Jost Tobias Springenberg
Jost Tobias Springenberg is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 30 papers that have together received 5.4k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (11 papers), Machine Learning and Algorithms (6 papers), Machine Learning and Data Classification (6 papers), Adversarial Robustness in Machine Learning (5 papers), Advanced Neural Network Applications (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Neural dynamics and brain function (3 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). The work is most often cited by research in Cognitive Neuroscience (2.0k citations), Human-Computer Interaction (410 citations) and Computer Vision and Pattern Recognition (1.5k citations). Jost Tobias Springenberg has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Frank Hutter, Katharina Eggensperger, Thomas Brox, Alexey Dosovitskiy, Wolfram Burgard, Martin Riedmiller, Lukas D. J. Fiederer, Michael Tangermann, Robin Tibor Schirrmeister and Tonio Ball. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Human Brain Mapping, KI - Künstliche Intelligenz, arXiv (Cornell University) and International Conference on Learning Representations.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.