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

First Page		Document Content
Date: 2018-05-14 04:41:41 Artificial neural networks Mathematics Computational neuroscience Applied mathematics Mathematical analysis Lipschitz continuity operator Continuous function Gradient descent Convolutional neural network Rectifier Deep learning		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 Add to Reading List Source URL: qav.comlab.ox.ac.uk Download Document from Source Website File Size: 1,23 MB Share Document on Facebook

	Exploratory Data Analysis Tools Stelian Ion∗ Technical Reports Abstract In this paper we review some mathematical tools to analyze ecological data. We focus on DocID: 1vqrO - View Document
	K. Murota, University of Tokyo, Japan Matrices and Matroids for Systems Analysis A matroid is an abstract mathematical structure that captures combinatorial properties of matrices. This book offers a unique introduction DocID: 1vdBT - View Document
	Network-Design Sensitivity Analysis Paul Tune and Matthew Roughan School of Mathematical Sciences The University of Adelaide, Australia {paul.tune,matthew.roughan}@adelaide.edu.au DocID: 1vdkB - View Document
	Universit¨at Stuttgart Institut fu¨r Systemtheorie und Regelungstechnik Prof. Dr.–Ing. Frank Allg¨ower Open Thesis (BA, MA, SA) Mathematical modeling and analysis of DocID: 1v77P - View Document
	Probability: Subjective and Mathematical Author(s): Peter J. R. Millican Source: Analysis, Vol. 44, No. 1 (Jan., 1984), ppPublished by: Oxford University Press on behalf of The Analysis Committee Stable URL: http DocID: 1v72E - View Document