Publications

2017

Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber: Neural Expectation Maximization In Advances in Neural Information Processing Systems 30 (NIPS 2017) pre-proceedings.
Klaus Greff, Aaron Klein, Martin Chovanec, Frank Hutter, Jürgen Schmidhuber: The Sacred Infrastructure for Computational Research In Proceedings of the 15th Python in Science Conference SciPy 2017.
Klaus Greff, Rupesh K. Srivastava, Jürgen Schmidhuber: Highway and residual networks learn unrolled iterative estimation In Proceedings of the International Conference on Learning Representations (ICLR 2017).

Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Jürgen Schmidhuber, Harri Valpola: Tagger: Deep Unsupervised Perceptual Grouping In Advances in Neural Information Processing Systems 29 (NIPS 2016) pre-proceedings. (longer) arXiv version
Jelena Luketina, Mathias Berglund, Klaus Greff, Tapani Raiko: Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters Proceedings of The 33rd International Conference on Machine Learning, pp. 2952–2960, 2016
Klaus Greff, Rupesh K. Srivastava, Jürgen Schmidhuber: Binding via Reconstruction Clustering In ICLR 2016 Workshop
Klaus Greff, Ruud van Damme, Jan Koutník, Hajo Broersma, Julia Mikhal, Celestine Lawrence, Wilfred van der Wiel, Jürgen Schmidhuber Unconventional Computing Using Evolution-in-Nanomaterio: Neural Networks meet Nanoparticle Networks In FUTURE COMPUTING 2016, The Eighth International Conference on Future Computational Technologies and Applications

Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber: Training Very Deep Networks In Advances in Neural Information Processing Systems 28 (NIPS 2015) pp. 2368-2376.
Klaus Greff, Jürgen Schmidhuber: Introducing Sacred: A Tool to Facilitate Reproducible Research In ICML 2015 AutoML Workshop
Rupesh K. Srivastava, Klaus Greff, Jürgen Schmidhuber: Highway Networks In ICML 2015 Deep Learning Workshop
Klaus Greff, Rupesh K. Srivastava, Jan Koutník, Jürgen Schmidhuber: LSTM: A Search Space Odyssey IEEE Transactions on Neural Networks and Learning Systems (pre-print) arXiv preprint arXiv:1503.04069

Jan Koutník, Klaus Greff, Faustino J. Gomez, Jürgen Schmidhuber: A Clockwork RNN. In Proceedings of The 31st International Conference on Machine Learning (pp. 1863-1871)

Daniel Engel, Klaus Greff, Christoph Garth, Keith Bein, Anthony S. Wexler, Bernd Hamann, Hans Hagen: Visual Steering and Verification of Mass Spectrometry Data Factorization in Air Quality Research. In IEEE Trans. Vis. Comput. Graph. 18(12): 2275-2284
Klaus Greff, André Brandão, Stephan Krauß, Didier Stricker, Esteban Clua: A Comparison between Background Subtraction Algorithms using a Consumer Depth Camera. VISAPP (1) 2012: 431-436