Download or read book Data Driven Computational Methods written by John Harlim and published by Cambridge University Press. This book was released on 2018-07-12 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes computational methods for parametric and nonparametric modeling of stochastic dynamics. Aimed at graduate students, and suitable for self-study.
Download or read book Data Driven Modeling Scientific Computation written by Jose Nathan Kutz and published by . This book was released on 2013-08-08 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine learning, this book develops techniques that allow for the integration of the dynamics of complex systems and big data. MATLAB is used throughout for mathematical solution strategies.
Download or read book Data Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Download or read book Data Driven Computational Neuroscience written by Concha Bielza and published by Cambridge University Press. This book was released on 2020-11-26 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trains researchers and graduate students in state-of-the-art statistical and machine learning methods to build models with real-world data.
Download or read book Computational and Data Driven Chemistry Using Artificial Intelligence written by Takashiro Akitsu and published by Elsevier. This book was released on 2021-10-08 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and current developments in the field, giving readers insight into how these tools can be harnessed to enhance their own work. Offering the ability to process large or complex data-sets, compare molecular characteristics and behaviors, and help researchers design or identify new structures, Artificial Intelligence (AI) holds huge potential to revolutionize the future of chemistry. Volume 1 explores the fundamental knowledge and current methods being used to apply AI across a whole host of chemistry applications. Drawing on the knowledge of its expert team of global contributors, the book offers fascinating insight into this rapidly developing field and serves as a great resource for all those interested in exploring the opportunities afforded by the intersection of chemistry and AI in their own work. Part 1 provides foundational information on AI in chemistry, with an introduction to the field and guidance on database usage and statistical analysis to help support newcomers to the field. Part 2 then goes on to discuss approaches currently used to address problems in broad areas such as computational and theoretical chemistry; materials, synthetic and medicinal chemistry; crystallography, analytical chemistry, and spectroscopy. Finally, potential future trends in the field are discussed. - Provides an accessible introduction to the current state and future possibilities for AI in chemistry - Explores how computational chemistry methods and approaches can both enhance and be enhanced by AI - Highlights the interdisciplinary and broad applicability of AI tools across a wide range of chemistry fields
Download or read book Data Driven Personas written by Bernard J. Jansen and published by Springer Nature. This book was released on 2022-05-31 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven personas are a significant advancement in the fields of human-centered informatics and human-computer interaction. Data-driven personas enhance user understanding by combining the empathy inherent with personas with the rationality inherent in analytics using computational methods. Via the employment of these computational methods, the data-driven persona method permits the use of large-scale user data, which is a novel advancement in persona creation. A common approach for increasing stakeholder engagement about audiences, customers, or users, persona creation remained relatively unchanged for several decades. However, the availability of digital user data, data science algorithms, and easy access to analytics platforms provide avenues and opportunities to enhance personas from often sketchy representations of user segments to precise, actionable, interactive decision-making tools—data-driven personas! Using the data-driven approach, the persona profile can serve as an interface to a fully functional analytics system that can present user representation at various levels of information granularity for more task-aligned user insights. We trace the techniques that have enabled the development of data-driven personas and then conceptually frame how one can leverage data-driven personas as tools for both empathizing with and understanding of users. Presenting a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes, we illustrate applying this framework via practical use cases in areas of system design, digital marketing, and content creation to demonstrate the application of data-driven personas in practical applied situations. We then present an overview of a fully functional data-driven persona system as an example of multi-level information aggregation needed for decision making about users. We demonstrate that data-driven personas systems can provide critical, empathetic, and user understanding functionalities for anyone needing such insights.
Download or read book Tensor Voting written by Philippos Mordohai and published by Springer Nature. This book was released on 2022-06-01 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: This lecture presents research on a general framework for perceptual organization that was conducted mainly at the Institute for Robotics and Intelligent Systems of the University of Southern California. It is not written as a historical recount of the work, since the sequence of the presentation is not in chronological order. It aims at presenting an approach to a wide range of problems in computer vision and machine learning that is data-driven, local and requires a minimal number of assumptions. The tensor voting framework combines these properties and provides a unified perceptual organization methodology applicable in situations that may seem heterogeneous initially. We show how several problems can be posed as the organization of the inputs into salient perceptual structures, which are inferred via tensor voting. The work presented here extends the original tensor voting framework with the addition of boundary inference capabilities; a novel re-formulation of the framework applicable to high-dimensional spaces and the development of algorithms for computer vision and machine learning problems. We show complete analysis for some problems, while we briefly outline our approach for other applications and provide pointers to relevant sources.
Download or read book Data Driven Methods for Adaptive Spoken Dialogue Systems written by Oliver Lemon and published by Springer Science & Business Media. This book was released on 2012-10-21 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present “end-to-end” in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
Download or read book Computational Legal Studies written by Ryan Whalen and published by Edward Elgar Publishing. This book was released on 2020-09-25 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring contributions from a diverse set of experts, this thought-provoking book offers a visionary introduction to the computational turn in law and the resulting emergence of the computational legal studies field. It explores how computational data creation, collection, and analysis techniques are transforming the way in which we comprehend and study the law, and the implications that this has for the future of legal studies.
Download or read book Dynamic Mode Decomposition written by J. Nathan Kutz and published by SIAM. This book was released on 2016-11-23 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven dynamical systems is a burgeoning field?it connects how measurements of nonlinear dynamical systems and/or complex systems can be used with well-established methods in dynamical systems theory. This is a critically important new direction because the governing equations of many problems under consideration by practitioners in various scientific fields are not typically known. Thus, using data alone to help derive, in an optimal sense, the best dynamical system representation of a given application allows for important new insights. The recently developed dynamic mode decomposition (DMD) is an innovative tool for integrating data with dynamical systems theory. The DMD has deep connections with traditional dynamical systems theory and many recent innovations in compressed sensing and machine learning. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems, the first book to address the DMD algorithm, presents a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development; blends theoretical development, example codes, and applications to showcase the theory and its many innovations and uses; highlights the numerous innovations around the DMD algorithm and demonstrates its efficacy using example problems from engineering and the physical and biological sciences; and provides extensive MATLAB code, data for intuitive examples of key methods, and graphical presentations.
Download or read book System and Data Driven Methods and Algorithms written by Peter Benner and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-11-08 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.
Download or read book Computational Epidemiology written by Ellen Kuhl and published by Springer Nature. This book was released on 2021-09-22 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This innovative textbook brings together modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science, and machine learning to understand one of the most significant problems of our current time, the outbreak dynamics and outbreak control of COVID-19. It teaches the relevant tools to model and simulate nonlinear dynamic systems in view of a global pandemic that is acutely relevant to human health. If you are a student, educator, basic scientist, or medical researcher in the natural or social sciences, or someone passionate about big data and human health: This book is for you! It serves as a textbook for undergraduates and graduate students, and a monograph for researchers and scientists. It can be used in the mathematical life sciences suitable for courses in applied mathematics, biomedical engineering, biostatistics, computer science, data science, epidemiology, health sciences, machine learning, mathematical biology, numerical methods, and probabilistic programming. This book is a personal reflection on the role of data-driven modeling during the COVID-19 pandemic, motivated by the curiosity to understand it.
Download or read book Theater as Data written by Miguel Escobar Varela and published by University of Michigan Press. This book was released on 2021-08-02 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Theater as Data, Miguel Escobar Varela explores the use of computational methods and digital data in theater research. He considers the implications of these new approaches, and explains the roles that statistics and visualizations play. Reflecting on recent debates in the humanities, the author suggests that there are two ways of using data, both of which have a place in theater research. Data-driven methods are closer to the pursuit of verifiable results common in the sciences; and data-assisted methods are closer to the interpretive traditions of the humanities. The book surveys four major areas within theater scholarship: texts (not only playscripts but also theater reviews and program booklets); relationships (both the links between fictional characters and the collaborative networks of artists and producers); motion (the movement of performers and objects on stage); and locations (the coordinates of performance events, venues, and touring circuits). Theater as Data examines important contributions to theater studies from similar computational research, including in classical French drama, collaboration networks in Australian theater, contemporary Portuguese choreography, and global productions of Ibsen. This overview is complemented by short descriptions of the author’s own work in the computational analysis of theater practices in Singapore and Indonesia. The author ends by considering the future of computational theater research, underlining the importance of open data and digital sustainability practices, and encouraging readers to consider the benefits of learning to code. A web companion offers illustrative data, programming tutorials, and videos.
Download or read book Computational Methods for Geodynamics written by Alik Ismail-Zadeh and published by Cambridge University Press. This book was released on 2010-07-22 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written as both a textbook and a handy reference, this text deliberately avoids complex mathematics assuming only basic familiarity with geodynamic theory and calculus. Here, the authors have brought together the key numerical techniques for geodynamic modeling, demonstrations of how to solve problems including lithospheric deformation, mantle convection and the geodynamo. Building from a discussion of the fundamental principles of mathematical and numerical modeling, the text moves into critical examinations of each of the different techniques before concluding with a detailed analysis of specific geodynamic applications. Key differences between methods and their respective limitations are also discussed - showing readers when and how to apply a particular method in order to produce the most accurate results. This is an essential text for advanced courses on numerical and computational modeling in geodynamics and geophysics, and an invaluable resource for researchers looking to master cutting-edge techniques. Links to supplementary computer codes are available online.
Download or read book Computational Materials Design written by Tetsuya Saito and published by Nelson Thornes. This book was released on 1999-07-23 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of ten chapters which outline a wide range of technologies from first-principle calculations to continuum mechanics, with applications to materials design and development. Written with a clear exposition, this book will be invaluable for engineers who want to learn about the modern technologies and techniques utilized in materials design.
Download or read book Computational Science ICCS 2004 written by Marian Bubak and published by Springer Science & Business Media. This book was released on 2004-05-26 with total page 1376 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conference on Computational Science (ICCS 2004) held in Krak ́ ow, Poland, June 6–9, 2004, was a follow-up to the highly successful ICCS 2003 held at two locations, in Melbourne, Australia and St. Petersburg, Russia; ICCS 2002 in Amsterdam, The Netherlands; and ICCS 2001 in San Francisco, USA. As computational science is still evolving in its quest for subjects of inves- gation and e?cient methods, ICCS 2004 was devised as a forum for scientists from mathematics and computer science, as the basic computing disciplines and application areas, interested in advanced computational methods for physics, chemistry, life sciences, engineering, arts and humanities, as well as computer system vendors and software developers. The main objective of this conference was to discuss problems and solutions in all areas, to identify new issues, to shape future directions of research, and to help users apply various advanced computational techniques. The event harvested recent developments in com- tationalgridsandnextgenerationcomputingsystems,tools,advancednumerical methods, data-driven systems, and novel application ?elds, such as complex - stems, ?nance, econo-physics and population evolution.
Download or read book Computational Methods for Integral Equations written by L. M. Delves and published by CUP Archive. This book was released on 1985 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a readable account of techniques for numerical solutions.
