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Sigurd Spieckermann
Sigurd Spieckermann
Principal Research Scientist @ SIEMENS
Email verificata su alumni.stanford.edu
Titolo
Citata da
Citata da
Anno
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv e-prints, arXiv: 1605.02688, 2016
9042016
Theano: A Python framework for fast computation of mathematical expressions
TTD Team, R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, ...
arXiv preprint arXiv:1605.02688, 2016
2052016
Theano: A Python framework for fast computation of mathematical expressions. arXiv
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv preprint arXiv:1605.02688 10, 2016
492016
Harm de Vries, David Warde-Farley, Dustin J
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, and …, 2016
302016
Theano: A Python framework for fast computation of mathematical expressions. arXiv e-prints, abs/1605.02688
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
URL http://arxiv. org/abs/1605.02688, 2016
232016
Exploiting Similarity in System Identification Tasks with Recurrent Neural Networks
S Spieckermann, S Düll, S Udluft, A Hentschel, T Runkler
Neurocomputing, 2015
162015
Exploiting Similarity in System Identification Tasks with Recurrent Neural Networks
S Spieckermann, S Düll, S Udluft, A Hentschel, T Runkler
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2014
162014
Theano: A Python framework for fast computation of mathematical expressions. arXiv e-prints, abs/1605.02688, May 2016
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
URL http://arxiv. org/abs/1605.02688. Project URL http://github. com/Theano …, 2016
112016
Controlling a Target System
S Düll, M Munshi, S Spieckermann, S Udluft
US Patent App. 14/258,740, 2015
82015
Data-Efficient Temporal Regression with Multi-Task Recurrent Neural Networks
S Spieckermann, S Udluft, T Runkler
Advances in Neural Information Processing Systems (NIPS), Second Workshop on …, 2014
62014
Attention-based Information Fusion using Multi-Encoder-Decoder Recurrent Neural Networks
S Baier, S Spieckermann, V Tresp
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2017
52017
Method, controller, and computer program product for controlling a target system
S Düll, M Munshi, S Spieckermann, S Udluft
US Patent App. 15/297,342, 2017
42017
Regularized Recurrent Neural Networks for Data Efficient Dual-Task Learning
S Spieckermann, S Düll, S Udluft, T Runkler
International Conference on Artificial Neural Networks (ICANN), 17-24, 2014
42014
Method and apparatus for determining a network topology of a hierarchical network
D Beyer, D Krompaß, S Spieckermann
US Patent 10,547,513, 2020
32020
Method and apparatus for optimizing diagnostics of rotating equipment
B Andrassy, R Arnatt, A Avdovic, M Buckley, F Buggenthin, ...
EP Patent App. 3223095A1, 2017
3*2017
Multi-System Identification for Efficient Knowledge Transfer with Factored Tensor Recurrent Neural Networks
S Spieckermann, S Düll, S Udluft, T Runkler
European Conference on Machine Learning (ECML), Workshop on Generalization …, 2014
32014
Automated Patent Classification
I Christopher, L Sydney, S Spieckermann
Stanford University, CS229: Machine Learning, 2011
32011
Multi-task and transfer learning with recurrent neural networks
S Spieckermann
Technische Universität München, 2015
12015
Method and apparatus for automatic identification of an outage of a network node
D Beyer, D Krompaß, S Spieckermann
US Patent 10,848,386, 2020
2020
Determining a network topology of a hierarchical power supply network
S Spieckermann, D Krompaß, D Beyer
EP Patent App. 3345342A1, 2018
2018
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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