Introduction To Neural Network Verification

Author : Aws Albarghouthi
Publisher : Unknown
Page : 182 pages
File Size : 53,6 Mb
Release : 2021-12-02
Category : Electronic
ISBN : 1680839101

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Introduction to Neural Network Verification by Aws Albarghouthi Pdf

Over the past decade, a number of hardware and software advances have conspired to thrust deep learning and neural networks to the forefront of computing. Deep learning has created a qualitative shift in our conception of what software is and what it can do: Every day we're seeing new applications of deep learning, from healthcare to art, and it feels like we're only scratching the surface of a universe of new possibilities. This book offers the first introduction of foundational ideas from automated verification as applied to deep neural networks and deep learning. It is divided into three parts: Part 1 defines neural networks as data-flow graphs of operators over real-valued inputs. Part 2 discusses constraint-based techniques for verification. Part 3 discusses abstraction-based techniques for verification. The book is a self-contained treatment of a topic that sits at the intersection of machine learning and formal verification. It can serve as an introduction to the field for first-year graduate students or senior undergraduates, even if they have not been exposed to deep learning or verification.

Author : Brian J. Taylor
Publisher : Springer Science & Business Media
Page : 280 pages
File Size : 45,6 Mb
Release : 2006-03-20
Category : Computers
ISBN : 9780387294858

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Methods and Procedures for the Verification and Validation of Artificial Neural Networks by Brian J. Taylor Pdf

Neural networks are members of a class of software that have the potential to enable intelligent computational systems capable of simulating characteristics of biological thinking and learning. Currently no standards exist to verify and validate neural network-based systems. NASA Independent Verification and Validation Facility has contracted the Institute for Scientific Research, Inc. to perform research on this topic and develop a comprehensive guide to performing V&V on adaptive systems, with emphasis on neural networks used in safety-critical or mission-critical applications. Methods and Procedures for the Verification and Validation of Artificial Neural Networks is the culmination of the first steps in that research. This volume introduces some of the more promising methods and techniques used for the verification and validation (V&V) of neural networks and adaptive systems. A comprehensive guide to performing V&V on neural network systems, aligned with the IEEE Standard for Software Verification and Validation, will follow this book.

Author : Laura L. Pullum,Brian J. Taylor,Marjorie A. Darrah
Publisher : John Wiley & Sons
Page : 146 pages
File Size : 51,6 Mb
Release : 2007-03-09
Category : Computers
ISBN : 9780470084571

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Guidance for the Verification and Validation of Neural Networks by Laura L. Pullum,Brian J. Taylor,Marjorie A. Darrah Pdf

This book provides guidance on the verification and validation of neural networks/adaptive systems. Considering every process, activity, and task in the lifecycle, it supplies methods and techniques that will help the developer or V&V practitioner be confident that they are supplying an adaptive/neural network system that will perform as intended. Additionally, it is structured to be used as a cross-reference to the IEEE 1012 standard.

Author : Alexandra Silva,K. Rustan M. Leino
Publisher : Springer Nature
Page : 922 pages
File Size : 54,5 Mb
Release : 2021-07-17
Category : Computers
ISBN : 9783030816858

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Computer Aided Verification by Alexandra Silva,K. Rustan M. Leino Pdf

This open access two-volume set LNCS 12759 and 12760 constitutes the refereed proceedings of the 33rd International Conference on Computer Aided Verification, CAV 2021, held virtually in July 2021. The 63 full papers presented together with 16 tool papers and 5 invited papers were carefully reviewed and selected from 290 submissions. The papers were organized in the following topical sections: Part I: invited papers; AI verification; concurrency and blockchain; hybrid and cyber-physical systems; security; and synthesis. Part II: complexity and termination; decision procedures and solvers; hardware and model checking; logical foundations; and software verification. This is an open access book.

Author : Kevin Gurney
Publisher : CRC Press
Page : 234 pages
File Size : 47,7 Mb
Release : 2018-10-08
Category : Computers
ISBN : 9781482286991

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An Introduction to Neural Networks by Kevin Gurney Pdf

Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.

Author : Shuvendu K. Lahiri,Chao Wang
Publisher : Springer Nature
Page : 682 pages
File Size : 50,9 Mb
Release : 2020-07-15
Category : Computers
ISBN : 9783030532888

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Computer Aided Verification by Shuvendu K. Lahiri,Chao Wang Pdf

The open access two-volume set LNCS 12224 and 12225 constitutes the refereed proceedings of the 32st International Conference on Computer Aided Verification, CAV 2020, held in Los Angeles, CA, USA, in July 2020.* The 43 full papers presented together with 18 tool papers and 4 case studies, were carefully reviewed and selected from 240 submissions. The papers were organized in the following topical sections: Part I: AI verification; blockchain and Security; Concurrency; hardware verification and decision procedures; and hybrid and dynamic systems. Part II: model checking; software verification; stochastic systems; and synthesis. *The conference was held virtually due to the COVID-19 pandemic.

Author : Sivanandam S., Paulraj M
Publisher : Vikas Publishing House
Page : 236 pages
File Size : 42,7 Mb
Release : 2009-11-01
Category : Computers
ISBN : 9788125914259

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Introduction to Artificial Neural Networks by Sivanandam S., Paulraj M Pdf

This fundamental book on Artificial Neural Networks has its emphasis on clear concepts, ease of understanding and simple examples. Written for undergraduate students, the book presents a large variety of standard neural networks with architecture, algorithms and applications.

Author : Changliu Liu,Tomer Arnon,Christopher Lazarus,Christopher Strong,Clark Barrett,Mykel J. Kochenderfer
Publisher : Unknown
Page : 128 pages
File Size : 52,5 Mb
Release : 2021-02-11
Category : Electronic
ISBN : 1680837869

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Algorithms for Verifying Deep Neural Networks by Changliu Liu,Tomer Arnon,Christopher Lazarus,Christopher Strong,Clark Barrett,Mykel J. Kochenderfer Pdf

Neural networks have been widely used in many applications, such as image classification and understanding, language processing, and control of autonomous systems. These networks work by mapping inputs to outputs through a sequence of layers. At each layer, the input to that layer undergoes an affine transformation followed by a simple nonlinear transformation before being passed to the next layer. Neural networks are being used for increasingly important tasks, and in some cases, incorrect outputs can lead to costly consequences, hence validation of correctness at each layer is vital. The sheer size of the networks makes this not feasible using traditional methods. In this monograph, the authors survey a class of methods that are capable of formally verifying properties of deep neural networks. In doing so, they introduce a unified mathematical framework for verifying neural networks, classify existing methods under this framework, provide pedagogical implementations of existing methods, and compare those methods on a set of benchmark problems. Algorithms for Verifying Deep Neural Networks serves as a tutorial for students and professionals interested in this emerging field as well as a benchmark to facilitate the design of new verification algorithms.

Author : Kristin Yvonne Rozier,Swarat Chaudhuri
Publisher : Springer Nature
Page : 508 pages
File Size : 40,7 Mb
Release : 2023-07-04
Category : Computers
ISBN : 9783031331701

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NASA Formal Methods by Kristin Yvonne Rozier,Swarat Chaudhuri Pdf

This book constitutes the proceedings of the 15th International Symposium on NASA Formal Methods, NFM 2023, held in Houston, Texas, USA, during May 16-18, 2023. The 26 full and 3 short papers presented in this volume were carefully reviewed and selected from 75 submissions. The papers deal with advances in formal methods, formal methods techniques, and formal methods in practice.

Author : Douglas J. Santry
Publisher : John Wiley & Sons
Page : 261 pages
File Size : 51,6 Mb
Release : 2023-12-12
Category : Computers
ISBN : 9781394205608

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Demystifying Deep Learning by Douglas J. Santry Pdf

Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software! The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial service, and science, for example. Just as the robot revolution threatened blue-collar jobs in the 1970s, so now the AI revolution promises a new era of productivity for white collar jobs. Important tasks have begun being taken over by ANNs, from disease detection and prevention to reading and supporting legal contracts, to understanding experimental data, model protein folding, and hurricane modeling. AI is everywhere—on the news, in think tanks, and occupies government policy makers all over the world —and ANNs often provide the backbone for AI. Relying on an informal and succinct approach, Demystifying Deep Learning is a useful tool to learn the necessary steps to implement ANN algorithms by using both a software library applying neural network training and verification software. The volume offers explanations of how real ANNs work, and includes 6 practical examples that demonstrate in real code how to build ANNS and the datasets they need in their implementation, available in open-source to ensure practical usage. This approachable book follows ANN techniques that are used every day as they adapt to natural language processing, image recognition, problem solving, and generative applications. This volume is an important introduction to the field equipping the reader for more advanced study. Demystifying Deep Learning readers will also find: A volume that emphasizes the importance of classification Discussion of why ANN libraries (such as Tensor Flow and Pytorch) are written in C++ rather than Python Each chapter concludes with a “Projects” page to promote students experimenting with real code A supporting library of software to accompany the book at https://github.com/nom-de-guerre/RANT Approachable explanation of how generative AI, such as generative adversarial networks (GAN) really work. An accessible motivation and elucidation of how transformers, the basis of large language models (LLM) such as ChatGPT, work. Demystifying Deep Learning is ideal for engineers and professionals that need to learn and understand ANNs in their work. It is also a helpful text for advanced undergraduates to get a solid grounding on the topic.

Author : Bistra Dilkina
Publisher : Springer Nature
Page : 332 pages
File Size : 40,5 Mb
Release : 2024-06-19
Category : Electronic
ISBN : 9783031605994

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Integration of Constraint Programming, Artificial Intelligence, and Operations Research by Bistra Dilkina Pdf

Author : Alexander Nadel ,Kristin Yvonne Rozier
Publisher : TU Wien Academic Press
Page : 332 pages
File Size : 45,7 Mb
Release : 2023-10-13
Category : Computers
ISBN : 9783854480600

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PROCEEDINGS OF THE 23RD CONFERENCE ON FORMAL METHODS IN COMPUTER-AIDED DESIGN – FMCAD 2023 by Alexander Nadel ,Kristin Yvonne Rozier Pdf

The Conference on Formal Methods in Computer-Aided Design (FMCAD) is an annual conference on the theory and applications of formal methods in hardware and system in academia and industry for presenting and discussing groundbreaking methods, technologies, theoretical results, and tools for reasoning formally about computing systems. FMCAD covers formal aspects of computer-aided system testing.

Author : Sharon Shoham,Yakir Vizel
Publisher : Springer Nature
Page : 563 pages
File Size : 45,8 Mb
Release : 2022-08-06
Category : Computers
ISBN : 9783031131851

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Computer Aided Verification by Sharon Shoham,Yakir Vizel Pdf

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book.

Author : Belgacem Ben Hedia,Yassine Maleh,Moez Krichen
Publisher : Springer Nature
Page : 192 pages
File Size : 51,5 Mb
Release : 2024-01-19
Category : Computers
ISBN : 9783031497377

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Verification and Evaluation of Computer and Communication Systems by Belgacem Ben Hedia,Yassine Maleh,Moez Krichen Pdf

This book constitutes the refereed proceedings of the 16th International Conference on Verification and Evaluation of Computer and Communication Systems, VECoS 2023, held in Marrakech, Morocco, during October 18–20, 2023. The 12 full papers included in this book were carefully reviewed and selected from 36 submissions. The topics presented covered a range of subjects, including approaches to improving the scalability and efficiency of formal verification and their applications to blockchain, smart contracts and neural networks.

Author : Yi Li,Sofiène Tahar
Publisher : Springer Nature
Page : 320 pages
File Size : 50,8 Mb
Release : 2023-11-09
Category : Computers
ISBN : 9789819975846

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Formal Methods and Software Engineering by Yi Li,Sofiène Tahar Pdf

This book constitutes the proceedings of the 24th International Conference on Formal Methods and Software Engineering, ICFEM 2023, held in Brisbane, QLD, Australia, during November 21–24, 2023. The 13 full papers presented together with 8 doctoral symposium papers in this volume were carefully reviewed and selected from 34 submissions, the volume also contains one invited paper. The conference focuses on applying formal methods to practical applications and presents papers for research in all areas related to formal engineering methods.