Jost Tobias Springenberg
Jost Tobias Springenberg
Verified email at informatik.uni-freiburg.de - Homepage
TitleCited byYear
Striving for simplicity: The all convolutional net
JT Springenberg, A Dosovitskiy, T Brox, M Riedmiller
arXiv preprint arXiv:1412.6806, 2014
18392014
Efficient and robust automated machine learning
M Feurer, A Klein, K Eggensperger, J Springenberg, M Blum, F Hutter
Advances in neural information processing systems, 2962-2970, 2015
5782015
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
5342015
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
4082017
Unsupervised and semi-supervised learning with categorical generative adversarial networks
JT Springenberg
arXiv preprint arXiv:1511.06390, 2015
4012015
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
3972015
Discriminative unsupervised feature learning with convolutional neural networks
A Dosovitskiy, JT Springenberg, M Riedmiller, T Brox
Advances in neural information processing systems, 766-774, 2014
3282014
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, 2746-2754, 2015
3222015
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
2172015
A learned feature descriptor for object recognition in rgb-d data
M Blum, JT Springenberg, J Wülfing, M Riedmiller
2012 IEEE International Conference on Robotics and Automation, 1298-1303, 2012
2092012
Initializing bayesian hyperparameter optimization via meta-learning
M Feurer, JT Springenberg, F Hutter
Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
1862015
Discriminative unsupervised feature learning with exemplar convolutional neural networks
A Dosovitskiy, P Fischer, JT Springenberg, M Riedmiller, T Brox
IEEE transactions on pattern analysis and machine intelligence 38 (9), 1734-1747, 2015
1582015
Learning to generate chairs, tables and cars with convolutional networks
A Dosovitskiy, JT Springenberg, M Tatarchenko, T Brox
IEEE transactions on pattern analysis and machine intelligence 39 (4), 692-705, 2016
1282016
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
992017
Learning by playing-solving sparse reward tasks from scratch
M Riedmiller, R Hafner, T Lampe, M Neunert, J Degrave, T Van de Wiele, ...
arXiv preprint arXiv:1802.10567, 2018
982018
Graph networks as learnable physics engines for inference and control
A Sanchez-Gonzalez, N Heess, JT Springenberg, J Merel, M Riedmiller, ...
arXiv preprint arXiv:1806.01242, 2018
972018
Towards automatically-tuned neural networks
H Mendoza, A Klein, M Feurer, JT Springenberg, F Hutter
Workshop on Automatic Machine Learning, 58-65, 2016
822016
Improving deep neural networks with probabilistic maxout units
JT Springenberg, M Riedmiller
arXiv preprint arXiv:1312.6116, 2013
812013
Maximum a posteriori policy optimisation
A Abdolmaleki, JT Springenberg, Y Tassa, R Munos, N Heess, ...
arXiv preprint arXiv:1806.06920, 2018
722018
Learning an embedding space for transferable robot skills
K Hausman, JT Springenberg, Z Wang, N Heess, M Riedmiller
682018
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