Jost Tobias Springenberg
Jost Tobias Springenberg
Verified email at informatik.uni-freiburg.de - Homepage
Title
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
20902014
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
7092015
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
5682015
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
5352017
Unsupervised and semi-supervised learning with categorical generative adversarial networks
JT Springenberg
arXiv preprint arXiv:1511.06390, 2015
4492015
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
4372015
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
3672014
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
3612015
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
2572015
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
2132012
Initializing bayesian hyperparameter optimization via meta-learning
M Feurer, JT Springenberg, F Hutter
Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2112015
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
2002015
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
1472016
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
1242018
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
1152018
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
1132017
Towards automatically-tuned neural networks
H Mendoza, A Klein, M Feurer, JT Springenberg, F Hutter
Workshop on Automatic Machine Learning, 58-65, 2016
1002016
Maximum a posteriori policy optimisation
A Abdolmaleki, JT Springenberg, Y Tassa, R Munos, N Heess, ...
arXiv preprint arXiv:1806.06920, 2018
872018
Improving deep neural networks with probabilistic maxout units
JT Springenberg, M Riedmiller
arXiv preprint arXiv:1312.6116, 2013
872013
Vlocnet++: Deep multitask learning for semantic visual localization and odometry
N Radwan, A Valada, W Burgard
IEEE Robotics and Automation Letters 3 (4), 4407-4414, 2018
79*2018
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