Neural networks

Results: 3500



#Item
1Reachability Analysis of Deep Neural Networks with Provable Guarantees Wenjie Ruan1 , Xiaowei Huang2 , Marta Kwiatkowska1 Department of Computer Science, University of Oxford, UK 2 Department of Computer Science, Univers

Reachability Analysis of Deep Neural Networks with Provable Guarantees Wenjie Ruan1 , Xiaowei Huang2 , Marta Kwiatkowska1 Department of Computer Science, University of Oxford, UK 2 Department of Computer Science, Univers

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Source URL: qav.comlab.ox.ac.uk

Language: English - Date: 2018-05-14 08:41:41
2Large Scale Training and Optimization of Neural Networks and Generative Adversarial Networks over Distributed Resource CLIC GAN : S. Vallecorsa, G. Khattak, F. Carminati, M. Pierini SurfSara : V. Codreanu, D. Podareanu

Large Scale Training and Optimization of Neural Networks and Generative Adversarial Networks over Distributed Resource CLIC GAN : S. Vallecorsa, G. Khattak, F. Carminati, M. Pierini SurfSara : V. Codreanu, D. Podareanu

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Source URL: indico.cern.ch

Language: English
3Deep Neural Networks Predict Category Typicality Ratings for Images Brenden M. Lake Wojciech Zaremba  Rob Fergus

Deep Neural Networks Predict Category Typicality Ratings for Images Brenden M. Lake Wojciech Zaremba Rob Fergus

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Source URL: cims.nyu.edu

Language: English - Date: 2015-05-04 19:17:21
4CogniSight SDK User’s Manual IMAGE RECOGNITION BASED ON NEUROMEM NEURAL NETWORKS Version 5.3

CogniSight SDK User’s Manual IMAGE RECOGNITION BASED ON NEUROMEM NEURAL NETWORKS Version 5.3

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Source URL: www.general-vision.com

Language: English - Date: 2018-09-10 17:57:45
5Blockchain For Financial Markets Applications and Services  Harnessing the Power of Artificial Intelligence, Neural Networks and Active Leverage “At its core Qompass will provide a rich ecosystem of API protocols and

Blockchain For Financial Markets Applications and Services Harnessing the Power of Artificial Intelligence, Neural Networks and Active Leverage “At its core Qompass will provide a rich ecosystem of API protocols and

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Source URL: icorating.com

Language: English
6This Talk § 1) Node embeddings § Map nodes to low-dimensional embeddings.  § 2) Graph neural networks

This Talk § 1) Node embeddings § Map nodes to low-dimensional embeddings. § 2) Graph neural networks

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Source URL: snap.stanford.edu

Language: English - Date: 2018-04-25 06:50:04
7Learning Inductive Biases with Simple Neural Networks Reuben Feinman () Center for Neural Science New York University Abstract People use rich prior knowledge about the world in order to

Learning Inductive Biases with Simple Neural Networks Reuben Feinman () Center for Neural Science New York University Abstract People use rich prior knowledge about the world in order to

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Source URL: cims.nyu.edu

Language: English - Date: 2018-06-05 18:44:05
8Poster: An Analysis of Targeted Password Guessing Using Neural Networks Huan Zhou, Qixu Liu, Fangjiao Zhang Institute of Information Engineering, Chinese Academy of Sciences School of Cyber Security, University of Chines

Poster: An Analysis of Targeted Password Guessing Using Neural Networks Huan Zhou, Qixu Liu, Fangjiao Zhang Institute of Information Engineering, Chinese Academy of Sciences School of Cyber Security, University of Chines

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Source URL: www.ieee-security.org

Language: English - Date: 2017-05-13 12:13:56
9Towards Evaluating the Robustness of Neural Networks Nicholas Carlini David Wagner University of California, Berkeley A BSTRACT

Towards Evaluating the Robustness of Neural Networks Nicholas Carlini David Wagner University of California, Berkeley A BSTRACT

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Source URL: www.ieee-security.org

Language: English - Date: 2017-04-03 20:02:30
10Mixture Density Networks Christopher M. Bishop Neural Computing Research Group Dept. of Computer Science and Applied Mathematics Aston University

Mixture Density Networks Christopher M. Bishop Neural Computing Research Group Dept. of Computer Science and Applied Mathematics Aston University

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Source URL: publications.aston.ac.uk

Language: English - Date: 2017-02-06 00:13:20