Juergen Schmidhuber

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Sepp HochreiterInstitute for Machine Learning, Johannes Kepler University LinzVerified email at ml.jku.at
Dan CiresanConndera ResearchVerified email at conndera.com
Alex GravesUniversity of TorontoVerified email at cs.toronto.edu
Faustino GomezCEO NNAISENSE SA. Former Senior Researcher, IDSIA, SwitzerlandVerified email at idsia.ch
luca maria gambardellaFaculty of informatics, USI, IDSIA - USI-SUPSI, Artificialy SA, LuganoVerified email at usi.ch
Rupesh Kumar SrivastavaNNAISENSEVerified email at nnaisense.com
Klaus GreffResearch Scientist at Google BrainVerified email at usi.ch
Felix GersProfessor of Computer Science, Berliner Hochschule für Technik (BHT)Verified email at felixgers.de
Jonathan MasciNNAISENSE SAVerified email at nnaisense.com
Daan WierstraPrincipal Scientist, DeepMindVerified email at google.com
Alessandro GiustiProfessor of AI for Autonomous Robotics, IDSIA, USI-SUPSI, Lugano, SwitzerlandVerified email at idsia.ch
Tom SchaulSenior Staff Scientist, DeepMindVerified email at nyu.edu
Jan KoutníkDirector of Intelligent Automation, NNAISENSEVerified email at idsia.ch
Santiago FernandezIK4-TeknikerVerified email at tekniker.es
Bas SteunebrinkJua.aiVerified email at jua.ai
Yi SunGoogleVerified email at idsia.ch
Alexander FörsterUniversity of BremenVerified email at uni-bremen.de
Frank SehnkeZentrum für Sonnenenergie- und Wasserstoff-Forschung StuttgartVerified email at in.tum.de
Kazuki IrieHarvard University, Center for Brain ScienceVerified email at fas.harvard.edu
Marco WieringInstitute of Artificial Intelligence and Cognitive Engineering, University of GroningenVerified email at rug.nl

Juergen Schmidhuber

King Abdullah University of Science and Technology / The Swiss AI Lab, IDSIA / University of Lugano

Verified email at kaust.edu.sa - Homepage

computer science artificial intelligence reinforcement learning neural networks physics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Long Short-Term Memory S Hochreiter, J Schmidhuber Neural Computation 9 (8), 1735–1780, 1997	120081	1997
Deep learning in neural networks: An overview J Schmidhuber Neural networks 61, 85-117, 2015	23937	2015
Learning to forget: Continual prediction with LSTM FA Gers, J Schmidhuber, F Cummins Neural computation 12 (10), 2451-2471, 2000	9077	2000
LSTM: A search space odyssey K Greff, RK Srivastava, J Koutník, BR Steunebrink, J Schmidhuber IEEE transactions on neural networks and learning systems 28 (10), 2222-2232, 2016	7878	2016
Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks A Graves, S Fernández, F Gomez, J Schmidhuber Proceedings of the 23rd international conference on Machine learning, 369-376, 2006	7391	2006
Multi-column deep neural network for traffic sign classification D CireşAn, U Meier, J Masci, J Schmidhuber Neural networks 32, 333-338, 2012	7316*	2012
Multi-column deep neural networks for image classification D Ciregan, U Meier, J Schmidhuber 2012 IEEE conference on computer vision and pattern recognition, 3642-3649, 2012	7178	2012
Framewise phoneme classification with bidirectional LSTM and other neural network architectures A Graves, J Schmidhuber Neural networks 18 (5-6), 602-610, 2005	6654	2005
Long short-term memory A Graves, A Graves Supervised sequence labelling with recurrent neural networks, 37-45, 2012	4283	2012
Training very deep networks RK Srivastava, K Greff, J Schmidhuber Advances in neural information processing systems 28, 2015	3472	2015
Gradient flow in recurrent nets: the difficulty of learning long-term dependencies S Hochreiter, Y Bengio, P Frasconi, J Schmidhuber A field guide to dynamical recurrent neural networks. IEEE Press, 2001	2809	2001
A novel connectionist system for unconstrained handwriting recognition A Graves, M Liwicki, S Fernández, R Bertolami, H Bunke, J Schmidhuber IEEE transactions on pattern analysis and machine intelligence 31 (5), 855-868, 2008	2796	2008
Stacked convolutional auto-encoders for hierarchical feature extraction J Masci, U Meier, D Cireşan, J Schmidhuber Artificial Neural Networks and Machine Learning–ICANN 2011: 21st …, 2011	2791	2011
Highway networks RK Srivastava, K Greff, J Schmidhuber arXiv preprint arXiv:1505.00387, 2015	2726	2015
Learning precise timing with LSTM recurrent networks FA Gers, NN Schraudolph, J Schmidhuber Journal of machine learning research 3 (Aug), 115-143, 2002	2273	2002
Flexible, high performance convolutional neural networks for image classification DC Ciresan, U Meier, J Masci, LM Gambardella, J Schmidhuber Twenty-second international joint conference on artificial intelligence, 2011	2264	2011
Deep neural networks segment neuronal membranes in electron microscopy images D Ciresan, A Giusti, L Gambardella, J Schmidhuber Advances in neural information processing systems 25, 2012	2171	2012
Mitosis detection in breast cancer histology images with deep neural networks DC Cireşan, A Giusti, LM Gambardella, J Schmidhuber Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013	1963	2013
Deep, big, simple neural nets for handwritten digit recognition DC Cireşan, U Meier, LM Gambardella, J Schmidhuber Neural computation 22 (12), 3207-3220, 2010	1677	2010
Offline handwriting recognition with multidimensional recurrent neural networks A Graves, J Schmidhuber Advances in neural information processing systems 21, 2008	1620	2008

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