Search results for "Deep Generative Modeling"
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Generative Art with JavaScript and SVG
This book introduces you to the exciting world of generative art (artwork that are solely or partially created with the use of an autonomous system) through the medium of SVG and JavaScript. More specifically, it will teach the use of Graphery SVG (gySVG), a JavaScript library that closely mirrors the SVG spec and makes scripting SVG very intuitive and enjoyable. Armed with gySVG, the reader will be taught tried and trusted techniques in producing generative imagery. Each chapter will build upon the previous one, and those completely new to programming will be given a primer to help them find their feet.Beginning with a simple generative sketch that illustrates, and then explains, fundamental programming concepts - such as variables, data types, operators, loops, conditionals and functions - the reader will go on to explore the power of Scalable Vector Graphics, how to play with randomness and regularity, how to use noise to create organic variance, and how to make sketches interactive and dynamic. More advanced topics will then be tackled, such as paths, filter effects, trigonometry, shape packing, flow fields and fractals.It will be a fun journey, easy to follow, peppered with plenty of attractive sketches throughout. The goal will be to visually inspire readers with compelling examples of what’s possible - rather than bare-bones, make-do illustrations - thereby breathing life into the underlying theoretical concepts.WHAT YOU'LL LEARN: Generative art is and its creative processHow to use the gySVG library locally with Node.js or online via CodepenConsolidation of JavaScript fundamentals, using modern ES6+ syntax Creating a variety of SVG shapes generatively Creating iterative variations of sketches by randomizing parametersUsing noise to create organic varianceCreating complex SVG paths generativelyHow to make sketches interactiveWHO IS IT FOR: Web developers and designers and creative coders with an interest in digital and generative art as well as artists who are interested in learning to code with JavaScript.
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Modeling for Insight
Praise for Modeling for Insight "Most books on modeling are either too theoretical or too focused on the mechanics of programming. Powell and Batt's emphasis on using simple spreadsheet models to gain business insight (which is, after all, the name of the game) is what makes this book stand head and shoulders above the rest. This clear and practical book deserves a place on the shelf of every business analyst." —Jonathan Koomey, PhD, Lawrence Berkeley National Laboratory and Stanford University, author of Turning Numbers into Knowledge: Mastering the Art of Problem Solving Most business analysts are familiar with using spreadsheets to organize data and build routine models. However, analysts often struggle when faced with examining new and ill-structured problems. Modeling for Insight is a one-of-a-kind guide to building effective spreadsheet models and using them to generate insights. With its hands-on approach, this book provides readers with an effective modeling process and specific modeling tools to become a master modeler. The authors provide a structured approach to problem-solving using four main steps: frame the problem, diagram the problem, build a model, and generate insights. Extensive examples, graduated in difficulty, help readers to internalize this modeling process, while also demonstrating the application of important modeling tools, including: Influence diagrams Spreadsheet engineering Parameterization Sensitivity analysis Strategy analysis Iterative modeling The real-world examples found in the book are drawn from a wide range of fields such as financial planning, insurance, pharmaceuticals, advertising, and manufacturing. Each chapter concludes with a discussion on how to use the insights drawn from these models to create an effective business presentation. Microsoft Office Excel and PowerPoint are used throughout the book, along with the add-ins Premium Solver, Crystal Ball, and Sensitivity Toolkit. Detailed appendices guide readers through the use of these software packages, and the spreadsheet models discussed in the book are available to download via the book's related Web site. Modeling for Insight is an ideal book for courses in engineering, operations research, and management science at the upper-undergraduate and graduate levels. It is also a valuable resource for consultants and business analysts who often use spreadsheets to better understand complex problems.
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Grundlagen Der Generativen Syntax
Das Buch führt grundlegend in die neuere generative Syntax ein. Ausgehend von Chomskys (1981) Prinzipien- und Parametertheorie werden die Weiterwicklung des Parameterbegriffs (Roberts 2019) und das Minimalistische Programm (Chomsky 2005) behandelt, das wegen der angenommenen Interaktion unterschiedlicher Module sprachlichen Wissens mit anderen Modellen wie der Optimalitätstheorie kompatibel ist. Der Band fasst zentrale Entwicklungsschritte syntaktischer Theoriebildung zusammen und diskutiert deren Anwendbarkeit auf die vergleichende Analyse romanischer Daten. Behandelt werden Themenfelder wie Wortstellung und Informationsstruktur, Pronomina, Adjektivstellung, sog. quirky subjects und flektierte Infinitive. Zudem werden Kaynes (1994) Antisymmetriehypothese und Rizzis (1997) Feinstruktur der Linken Satzperipherie diskutiert. Die Darstellung orientiert sich an in der universitären Lehre erprobten Konzepten und erlaubt sowohl die Verwendung des Bandes in Anfängerkursen als auch die vertiefende Nutzung durch Fortgeschrittene. Die Neuauflage bezieht neben dem Französischen, Italienischen und Spanischen auch das Portugiesische mit ein, wobei die Darstellung der europäischen und brasilianischen Varietät gleichberechtigt verpflichtet ist.
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Theory Of Cognitive Chasms: Delivering Business Value From Genai
This comprehensive book provides a research-backed framework explaining why GenAI adoptions routinely fail to deliver business value across enterprises. Based on a grounded theory approach, it identifies four major failure modes, or the Cognitive Chasms, that represent exponential risks to adoption.The scope details the complete causal framework, including antecedents, moderators, consequents and the core mediator, Cognitive Decision-Making, which marks the boundary condition of successful GenAI adoptions. The volume also proposes a Multistage Scaling Strategy (a dynamic roadmap for enterprise adoption) and essential Cognitive Mindsets (attitudes and beliefs integral to GenAI adoption) to successfully cross the cognitive chasms.Serving as a prescriptive field manual, this useful handbook benefits professionals, researchers, academics, postgraduate and graduate students in the fields of AI, technology/information management, organization behavior and business strategy and management.
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Generative AI for Transformational Management
The business world today is changing at a breakneck pace. Traditional management practices need help keeping up with the uncertainties and complexities of the digital age. Leaders face a lot of pressure to innovate, adapt, and drive transformative change within their organizations. However, they need more than just conventional wisdom to navigate this terrain. A deep understanding of emerging technologies like artificial intelligence (AI) and their practical applications in management is essential. Generative AI for Transformational Management offers a compelling solution to these challenges. This book provides a roadmap for leveraging AI to drive organizational transformation by exploring the intersection of generative AI and visionary leadership. By examining real-world case studies and practical applications, readers can learn how AI can be integrated into leadership practices to promote innovation and proactive decision-making and effectively navigate the complexities of the digital age. This book goes beyond theoretical exploration to be a practical guide that empowers leaders to harness AI's full potential in driving transformative outcomes. By providing a comprehensive understanding of generative AI and its impact on management, Generative AI for Transformational Management equips readers with the knowledge and tools they need to thrive in today's dynamic business environment.
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Speech Prosody in Speech Synthesis: Modeling and generation of prosody for high quality and flexible speech synthesis
The volume addresses issues concerning prosody generation in speech synthesis, including prosody modeling, how we can convey para- and non-linguistic information in speech synthesis, and prosody control in speech synthesis (including prosody conversions). A high level of quality has already been achieved in speech synthesis by using selection-based methods with segments of human speech. Although the method enables synthetic speech with various voice qualities and speaking styles, it requires large speech corpora with targeted quality and style.Accordingly, speech conversion techniques are now of growing interest among researchers. HMM/GMM-based methods are widely used, but entail several major problems when viewed from the prosody perspective; prosodic features cover a wider time span than segmental features and their frame-by-frame processing is not always appropriate. The book offers a good overview of state-of-the-art studies on prosody in speech synthesis.
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Regulating Hate Speech Created by Generative AI
Regulating Hate Speech Created by Generative AI explores the new hybrid space of Human Machine Interaction (HMI) in which hate speech is represented and computed through algorithms and AI generative systems. The book is exploratory because there are still many problem-solving challenges to be faced. It is also innovative because it is not assuming that solutions lie only in technological advancements but on a broader scale. In this sense, large language models can and are being considered from a holistic view (i.e., from the different dimensions and layers of regulatory and legal governance). Highlights of the book include:Generative AI and social engines of hateAn introduction to generative Artificial Intelligence application, trends, and ethicsThe mechanics and validation of generative AI outcomesAn evaluation of Generative AI for hate speech detectionBest practices and key considerations for AI regulationUsing GenAI capabilities for early detection of threats in the digital environment.This book is a hard look at ways to regulate generative AI to reduce online hate and secure justice in a digital environment. Featuring research and offering practical guidelines, the book examines guidelines for regulating generative AI models, so they do not contribute to online hate disinformation and imagery.
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Generative Complexity in a Complex Generative World
This book introduces a refreshing approach to twenty-first-century scientific approach in an age, which is also known as the Century of Complexity. It deals with the deep problem of complexity, being operative from the bottom-up. The current lack of understanding of complexity has led scholars into the so-called embarrassment of complexity. A long overdue paradigm shift is necessary to address complexity as generative complexity and brings readers to the edge of a scientific revolution: that is, a generative revolution in the Century of Complexity. The book offers a radical shift of paradigm from the paradigm of simplifying into the new generative paradigm of complexifying about processes that develop from the bottom-up. The book links complex generative reality with a corresponding radical new generative nature of order and explores new fronts in science. This book explores innovative concepts of interaction, of causality, of the unit of study, and of reality itself and enables readers to see complexity as generative, emergent complexity as being operative from the bottom-up. The book discusses and suggests solutions for the problem of complexity in this Century of Complexity. The author provides a new understanding of complexity based on a generative flux of forces and relations. The book aims to bring about a fundamental and foundational change in how we view and ‘do’ science for an interdisciplinary audience of academics ranging from social science and humanities to economy and biology.
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Modeling and Simulation of Complex Systems
Robert Siegfried presents a framework for efficient agent-based modeling and simulation of complex systems. He compares different approaches for describing structure and dynamics of agent-based models in detail. Based on this evaluation the author introduces the “General Reference Model for Agent-based Modeling and Simulation” (GRAMS). Furthermore he presents parallel and distributed simulation approaches for execution of agent-based models –from small scale to very large scale. The author shows how agent-based models may be executed by different simulation engines that utilize underlying hardware resources in an optimized fashion.
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Modeling and Managing Shallow Lake Eutrophication
In the late 1970s. the adverse effects of man-made eutrophication became manifest in many countries. which explains. perhaps. why there was such a broad interest when the former Resources and Environment Area of the International Institute for Applied Systems Analysis (IIASA) organized a workshop on the subject. There was such an enthusiasm among the partici pants that two further workshops were quickly organized. one on deep and the other on shallow lake eutrophication problems. The organization of these meetings was extremely stimulating. and the round table discussions among scientists from both West and East remain thought provoking for those who took part. The general feeling emerged that the complexity and multifaceted nature of the problem, even though perhaps not fully recognized at that time. clearly demanded a systems analysis approach. No wonder. then. that the request made by the Hungarian Member Organization of nASA to adopt Lake Balaton as a "real life laboratory" for an nASA case study fell on fertile ground. the more so since it appeared that shallow lake eutrophication had received less attention and was less well understood than that of deep lakes. And so the nASA Lake Balaton Case Study began. with the appointment of Gerrit van Straten as the first leader of the project.
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Credit Risk Modeling
Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand, and on a direct modeling of the default probability of issuers on the other. He offers insights that can be drawn from each approach and demonstrates that the distinction between the two approaches is not at all clear-cut. The book strikes a fruitful balance between quickly presenting the basic ideas of the models and offering enough detail so readers can derive and implement the models themselves. The discussion of the models and their limitations and five technical appendixes help readers expand and generalize the models themselves or to understand existing generalizations.The book emphasizes models for pricing as well as statistical techniques for estimating their parameters. Applications include rating-based modeling, modeling of dependent defaults, swap- and corporate-yield curve dynamics, credit default swaps, and collateralized debt obligations.
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Adaptive Regression for Modeling Nonlinear Relationships
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet nonlinear relationships are common and so need to be addressed. A standard linear analysis can produce misleading conclusions, while a nonlinear analysis can provide novel insights into data, not otherwise possible. A variety of examples of the benefits of modeling nonlinear relationships are presented throughout the book. Methods are covered using what are called fractional polynomials based on real-valued power transformations of primary predictor variables combined with model selection based on likelihood cross-validation. The book covers how to formulate and conduct such adaptive fractional polynomial modeling in the standard, logistic, and Poisson regression contexts with continuous, discrete, and counts outcomes, respectively, either univariate or multivariate. The book also provides a comparison of adaptive modeling to generalized additive modeling (GAM) and multiple adaptive regression splines (MARS) for univariate outcomes. The authors have created customized SAS macros for use in conducting adaptive regression modeling. These macros and code for conducting the analyses discussed in the book are available through the first author's website and online via the book’s Springer website. Detailed descriptions of how to use these macros and interpret their output appear throughout the book. These methods can be implemented using other programs.
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Pioneering Applications of Generative AI
Integrating generative artificial intelligence (AI) into art, design, and media presents a double-edged sword. While it offers unprecedented creative possibilities, it raises ethical concerns, challenges traditional workflows, and requires careful regulation. As AI becomes more prevalent in these fields, there is a pressing need for a comprehensive resource that explores the technology's potential and navigates the complex landscape of its implications. The Pioneering Applications of Generative AI is a pioneering book that addresses these challenges head-on. It provides a deep dive into the evolution, ethical considerations, core technologies, and creative applications of generative AI, offering readers a thorough understanding of this transformative technology. By showcasing cutting-edge research and innovative use cases, the book bridges academia and practice, fostering cross-disciplinary collaboration and pushing the boundaries of creativity. Researchers, academicians, scientists, and research scholars will find this book invaluable in navigating the complexities of generative AI in art, design, and media. With its focus on ethical and responsible AI and discussions on regulatory frameworks, the book equips readers with the knowledge and tools needed to harness the full potential of generative AI while ensuring its responsible and ethical use.
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Modeling from Reality
This book summarizes the results of our modeling-from-reality (MFR) project which took place over the last decade or so. The goal of this project is to develop techniques for modeling real objects and/or environments into geometric and photometric models through computer vision techniques. By developing such techniques, time consuming modeling process, currently un dertaken by human programmers, can be (semi-)automatically performed, and, as a result, we can drastically shorten the developing time of such virtual reality systems, reduce their developing cost, and widen their application areas. Originally, we began to develop geometric modeling techniques that acquire shape information of objects/environments for object recognition. Soon, this effort evolved into an independent modeling project, virtual-reality modeling, with the inclusion of photometric modeling aspects that acquire appearance information, such as color, texture, and smoothness. Over the course of this development, it became apparent that environmental modeling techniques were necessary when applying our techniques to mixed realities that seamlessly combine generated virtual models with other real/virtual images. The material in his book covers these aspects of development.
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Theoretical Alternatives to the Psychiatric Model of Mental Disorder Labeling
Theoretical Alternatives to the Psychiatric Model of Mental Disorder Labeling is the fourth Volume of the Ethics International Press Critical Psychology and Critical Psychiatry Series. Understanding the current systems of psychology and psychiatry is profoundly important. So is exploring alternatives. The Critical Psychology and Critical Psychiatry Series presents solicited chapters from international experts on a wide variety of underexplored subjects. This is a series for mental health researchers, teachers, and practitioners, for parents and interested lay readers, and for anyone trying to make sense of anxiety, depression, and other emotional difficulties. Theoretical Alternatives recognizes and appreciates those who have contributed to the abundance of literature critiquing the American Psychiatric Association s Diagnostic and Statistical Manual of Mental Disorders (DSM), the biomedical model of mental health, and the practice of psychiatric diagnosing. It intends to move past that discourse, and present macro and system-level alternatives to DSM and the ICD diagnosing (the World Health Organization s International Statistical Classification of Diseases and Related Health Problems), in the form of conceptually developed frameworks, taxonomies, and models to guide clinical work and theory.
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GLIM 82: Proceedings of the International Conference on Generalised Linear Models
This volume of Lecture Notes in Statistics consists of the published proceedings of the first international conference to be held on the topic of generalised linear models. This conference was held from 13 - 15 September 1982 at the Polytechnic of North London and marked an important stage in the development and expansion of the GLIM system. The range of the new system, tentatively named Prism, is here outlined by Bob Baker. Further sections of the volume are devoted to more detailed descriptions of the new facilities, including information on the two different numerical methods now available. Most of the data analyses in this volume are carried out using the GLIM system but this is, of course, not necessary. There are other ways of analysing generalised linear models and Peter Green here discusses the many attractive features of APL, including its ability to analyse generalised linear models. Later sections of the volume cover other invited and contributed papers on the theory and application of generalised linear models. Included amongst these is a paper by Murray Aitkin, proposing a unified approach to statistical modelling through direct likelihood inference, and a paper by Daryl Pregibon showing how GLIM can be programmed to carry out score tests. A paper by Joe Whittaker extends the recent discussion of the relationship between conditional independence and log-linear models and John Hinde considers the introduction of an independent random variable into a linear model to allow for unexplained variation in Poisson data.
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Verification by Error Modeling
This book presents the basis for reusing the test vector generation and simulation for the purpose of implementation verification, to result in a significant timesaving. It brings the results in the direction of merging manufacturing test vector generation and verification.
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Cooperative Decision-Making Modeling for Manned and Unmanned Aerial Vehicles
Focusing on “human-in-the-loop” and “human-on-the-loop” mechanisms, cognitive intelligent interaction, and the practical modeling, implementation, and application of limited human intervention in modern aerial systems, this book explores cooperative decision-making technologies between manned and unmanned aerial vehicles.It systematically discusses two primary approaches to cooperative decision-making mechanisms: limited human intervention and cognitive intelligent interaction. The authors introduce modeling methods for applying limited intervention in typical mission scenarios, such as obstacle avoidance, threat mitigation, and attack decision-making. They also explain how to assess human workload and cognitive load in manned-unmanned operations. Additionally, it outlines interactive cognitive models that support situational awareness, threat evaluation, task allocation, route planning, and decision simulation. These insights address the growing need for effective human-machine collaboration in complex operational environments driven by rapid advancements in information science, control science, cognitive science, and artificial intelligence.This title will appeal to researchers, engineers, and professionals specializing in command-and-control systems and intelligent decision-making systems. It will also serve as an essential reference for students and educators in information-related disciplines.
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Generative Programming and Component Engineering
This volume constitutes the proceedings of the second International Conference on Generative Programming and Component Engineering (GPCE 2003), held September 22–25, 2003, in Erfurt, Germany, sponsored by the NetObjectDays German industrial software development event, in cooperation with the ACM SIGPLAN and SIGSOFT societies. GPCE was created as an e?ort to bring - getherresearchersworkingonboththeprogramminglanguagesandthesoftware engineeringsideofprogramgenerationandcomponentengineering. Thecommon theme of program generation and component engineering is the domain-speci?c nature of both approaches. Depending on the characteristics of a domain, either a generative or a compositional technical solution may be appropriate. In just its second year, GPCE has shown a lot of promise for building a strong community. The response to the call for papers was excellent, with 62 submissions to the technical program, 2 of which were later withdrawn. Each paper received between three and ?ve reviews, many of them quite thorough and hopefully valuable to all authors. The electronic meeting allowed for - depthdiscussionsofallsubmissions,oftentoamuchgreaterextentthanpossible in a physical PC meeting. As a result, 21 papers were selected for presentation at the conference and are included in this volume, together with abstracts for the invited talks by Olivier Danvy and Peri Tarr. Of the accepted papers, 3 are co-authored by PC members (from a total of 5 PC submissions). We tried hard to ensure fairness and hold PC submissions to a high standard. The EDAS conference submission system was used to manage the paper submissions. Our EDAS installation was supported by Blair MacIntyre, who was particularlyhelpfulinresolvingtechnicalissueswiththesystem.
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