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Jost Tobias Springenberg
Jost Tobias Springenberg
Google DeepMind
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Cited by
Cited by
Year
Striving for simplicity: The all convolutional net
JT Springenberg, A Dosovitskiy, T Brox, M Riedmiller
arXiv preprint arXiv:1412.6806, 2014
61072014
Deep learning with convolutional neural networks for EEG decoding and visualization
RT Schirrmeister, JT Springenberg, LDJ Fiederer, M Glasstetter, ...
Human brain mapping 38 (11), 5391-5420, 2017
29752017
Efficient and robust automated machine learning
M Feurer, A Klein, K Eggensperger, J Springenberg, M Blum, F Hutter
Advances in neural information processing systems 28, 2015
28792015
Discriminative unsupervised feature learning with convolutional neural networks
A Dosovitskiy, JT Springenberg, M Riedmiller, T Brox
Advances in neural information processing systems 27, 2014
20102014
Learning to generate chairs with convolutional neural networks
A Dosovitskiy, J Tobias Springenberg, T Brox
Proceedings of the IEEE conference on computer vision and pattern …, 2015
10552015
Unsupervised and semi-supervised learning with categorical generative adversarial networks
JT Springenberg
arXiv preprint arXiv:1511.06390, 2015
9922015
Embed to control: A locally linear latent dynamics model for control from raw images
M Watter, J Springenberg, J Boedecker, M Riedmiller
Advances in neural information processing systems 28, 2015
9622015
A generalist agent
S Reed, K Zolna, E Parisotto, SG Colmenarejo, A Novikov, G Barth-Maron, ...
arXiv preprint arXiv:2205.06175, 2022
9332022
Multimodal deep learning for robust RGB-D object recognition
A Eitel, JT Springenberg, L Spinello, M Riedmiller, W Burgard
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
8012015
Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves
T Domhan, JT Springenberg, F Hutter
Twenty-fourth international joint conference on artificial intelligence, 2015
7962015
Graph networks as learnable physics engines for inference and control
A Sanchez-Gonzalez, N Heess, JT Springenberg, J Merel, M Riedmiller, ...
International conference on machine learning, 4470-4479, 2018
7412018
Initializing bayesian hyperparameter optimization via meta-learning
M Feurer, J Springenberg, F Hutter
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
5832015
Bayesian optimization with robust Bayesian neural networks
JT Springenberg, A Klein, S Falkner, F Hutter
Advances in neural information processing systems 29, 2016
5532016
Maximum a posteriori policy optimisation
A Abdolmaleki, JT Springenberg, Y Tassa, R Munos, N Heess, ...
arXiv preprint arXiv:1806.06920, 2018
5332018
Learning by playing solving sparse reward tasks from scratch
M Riedmiller, R Hafner, T Lampe, M Neunert, J Degrave, T Wiele, V Mnih, ...
International conference on machine learning, 4344-4353, 2018
5082018
Towards automatically-tuned neural networks
H Mendoza, A Klein, M Feurer, JT Springenberg, F Hutter
Workshop on automatic machine learning, 58-65, 2016
3712016
Learning an embedding space for transferable robot skills
K Hausman, JT Springenberg, Z Wang, N Heess, M Riedmiller
International Conference on Learning Representations, 2018
3542018
Critic regularized regression
Z Wang, A Novikov, K Zolna, JS Merel, JT Springenberg, SE Reed, ...
Advances in Neural Information Processing Systems 33, 7768-7778, 2020
3402020
Keep doing what worked: Behavioral modelling priors for offline reinforcement learning
NY Siegel, JT Springenberg, F Berkenkamp, A Abdolmaleki, M Neunert, ...
arXiv preprint arXiv:2002.08396, 2020
3122020
Deep reinforcement learning with successor features for navigation across similar environments
J Zhang, JT Springenberg, J Boedecker, W Burgard
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017
3092017
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