Zhiyuan Gong's Books

Fish Development and Genetics

The Zebrafish and Medaka Models

By: Zhiyuan Gong,Vladimir Korzh

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Fish Development and Genetics

The Zebrafish and Medaka Models

By: Zhiyuan Gong,Vladimir Korzh

The zebrafish is the most important fish model in developmental and genetic analyses. This book contains 19 review articles covering a broad spectrum of topics, from development to genetic tools. The contents range from early development, the role of maternal factors and gastrulation, to tissue differentiation and organogenesis, such as development of the organizer, notochord, floor plate, nervous system, somites, muscle, skeleton and endoderm. The genetic tools cover morpholino knock-down, transgenics, fish cloning, transposons and genome evolution. The book also includes two chapters on genome mapping and embryonic stem cells in medaka, another important model fish. Summarizing the state-of-the-art studies of the zebrafish model and focusing on the molecular aspects of development, this book is a valuable reference for students learning the basic aspects of the zebrafish model, and for researchers seeking resources in zebrafish research.

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Page Count

684

Publisher

World Scientific

Published Date

ISBN 10

9812388214

ISBN 13

9789812388216

Lifelong Machine Learning

By: Zhiyuan Chaudhri,Bing Liu

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Lifelong Machine Learning

By: Zhiyuan Chaudhri,Bing Liu

Lifelong Machine Learning (or Lifelong Learning) is an advanced machine learning paradigm that learns continuously, accumulates the knowledge learned in previous tasks, and uses it to help future learning. In the process, the learner becomes more and more knowledgeable and effective at learning. This learning ability is one of the hallmarks of human intelligence. However, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model. It makes no attempt to retain the learned knowledge and use it in future learning. Although this isolated learning paradigm has been very successful, it requires a large number of training examples, and is only suitable for well-defined and narrow tasks. In comparison, we humans can learn effectively with a few examples because we have accumulated so much knowledge in the past which enables us to learn with little data or effort. Lifelong learning aims to achieve this capability. As statistical machine learning matures, it is time to make a major effort to break the isolated learning tradition and to study lifelong learning to bring machine learning to new heights. Applications such as intelligent assistants, chatbots, and physical robots that interact with humans and systems in real-life environments are also calling for such lifelong learning capabilities. Without the ability to accumulate the learned knowledge and use it to learn more knowledge incrementally, a system will probably never be truly intelligent. This book serves as an introductory text and survey to lifelong learning.

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Page Count

137

Publisher

Springer Nature

Published Date

ISBN 10

3031015754

ISBN 13

9783031015755

Lifelong Machine Learning, Second Edition

By: Zhiyuan Sun,Bing Leno da Silva

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Lifelong Machine Learning, Second Edition

By: Zhiyuan Sun,Bing Leno da Silva

Lifelong Machine Learning, Second Edition is an introduction to an advanced machine learning paradigm that continuously learns by accumulating past knowledge that it then uses in future learning and problem solving. In contrast, the current dominant machine learning paradigm learns in isolation: given a training dataset, it runs a machine learning algorithm on the dataset to produce a model that is then used in its intended application. It makes no attempt to retain the learned knowledge and use it in subsequent learning. Unlike this isolated system, humans learn effectively with only a few examples precisely because our learning is very knowledge-driven: the knowledge learned in the past helps us learn new things with little data or effort. Lifelong learning aims to emulate this capability, because without it, an AI system cannot be considered truly intelligent. Research in lifelong learning has developed significantly in the relatively short time since the first edition of this book was published. The purpose of this second edition is to expand the definition of lifelong learning, update the content of several chapters, and add a new chapter about continual learning in deep neural networks—which has been actively researched over the past two or three years. A few chapters have also been reorganized to make each of them more coherent for the reader. Moreover, the authors want to propose a unified framework for the research area. Currently, there are several research topics in machine learning that are closely related to lifelong learning—most notably, multi-task learning, transfer learning, and meta-learning—because they also employ the idea of knowledge sharing and transfer. This book brings all these topics under one roof and discusses their similarities and differences. Its goal is to introduce this emerging machine learning paradigm and present a comprehensive survey and review of the important research results and latest ideas in the area. This book is thus suitable for students, researchers, and practitioners who are interested in machine learning, data mining, natural language processing, or pattern recognition. Lecturers can readily use the book for courses in any of these related fields.

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Page Count

187

Publisher

Springer Nature

Published Date

ISBN 10

3031015819

ISBN 13

9783031015816

Paper Tiger

Inside the Real China

By: Xu Zhiyuan

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Paper Tiger

Inside the Real China

By: Xu Zhiyuan

In PAPER TIGER the Chinese journalist and intellectual Xu Zhiyuan paints a portrait of the world's second-largest economy via a thoughtful and wide-ranging series of mini essays on contemporary Chinese society. Xu Zhiyuan describes the many stages upon which China's great transformation is taking place, from Beijing's Silicon district to a cruise down the Three Gorges; he profiles China's dissidents, including Liu Xiaobo, Ai Weiwei and Chen Guangcheng; and explores lesser-known stories of scandals that rocked China but which most people outside that country did not hear about – and which shed troubling light on China's dark heart. Xu Zhiyuan understands his homeland in a way no foreign correspondent ever could. PAPER TIGER is a unique insider's view of China that is measured and brave, ambitious in scope and deeply personal.

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Page Count

349

Publisher

Bloomsbury Publishing

Published Date

ISBN 10

1781859817

ISBN 13

9781781859810

Introduction to Graph Neural Networks

By: Zhiyuan Zhiyuan Liu,Jie Jie Zhou

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Introduction to Graph Neural Networks

By: Zhiyuan Zhiyuan Liu,Jie Jie Zhou

Graphs are useful data structures in complex real-life applications such as modeling physical systems, learning molecular fingerprints, controlling traffic networks, and recommending friends in social networks. However, these tasks require dealing with non-Euclidean graph data that contains rich relational information between elements and cannot be well handled by traditional deep learning models (e.g., convolutional neural networks (CNNs) or recurrent neural networks (RNNs)). Nodes in graphs usually contain useful feature information that cannot be well addressed in most unsupervised representation learning methods (e.g., network embedding methods). Graph neural networks (GNNs) are proposed to combine the feature information and the graph structure to learn better representations on graphs via feature propagation and aggregation. Due to its convincing performance and high interpretability, GNN has recently become a widely applied graph analysis tool. This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN model. Then several variants of the vanilla model are introduced such as graph convolutional networks, graph recurrent networks, graph attention networks, graph residual networks, and several general frameworks. Variants for different graph types and advanced training methods are also included. As for the applications of GNNs, the book categorizes them into structural, non-structural, and other scenarios, and then it introduces several typical models on solving these tasks. Finally, the closing chapters provide GNN open resources and the outlook of several future directions.

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Page Count

109

Publisher

Springer Nature

Published Date

ISBN 10

3031015878

ISBN 13

9783031015878

Representation Learning for Natural Language Processing

By: Zhiyuan Liu,Yankai Lin,Maosong Sun

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Representation Learning for Natural Language Processing

By: Zhiyuan Liu,Yankai Lin,Maosong Sun

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.

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Page Count

319

Publisher

Springer Nature

Published Date

ISBN 10

9811555737

ISBN 13

9789811555732

Natural Gas Hydrate Management in Deepwater Gas Well

By: Zhiyuan Wang,Baojiang Sun,Yonghai Gao

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Natural Gas Hydrate Management in Deepwater Gas Well

By: Zhiyuan Wang,Baojiang Sun,Yonghai Gao

This book chiefly describes the theories and technologies for natural gas hydrate management in deepwater gas wells. It systematically explores the mechanisms of hydrate formation, migration, deposition and blockage in multiphase flow in gas-dominated systems; constructs a multiphase flow model of multi-component systems for wells that takes into account hydrate phase transition; reveals the influence of hydrate phase transition on multiphase flows, and puts forward a creative hydrate blockage management method based on hydrate blockage free window (HBFW), which enormously improves the hydrate prevention effect in deepwater wells. The book combines essential theories and industrial technology practice to facilitate a deeper understanding of approaches to and technologies for hydrate management in deepwater wells, and provides guidance on operation design. Accordingly, it represents a valuable reference guide for both researchers and graduate students working in oil and gas engineering, offshore oil and gas engineering, oil and gas storage and transportation engineering, as well as technical staff in the fields of deepwater oil and gas drilling, development, and flow assurance.

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Page Count

242

Publisher

Springer Nature

Published Date

ISBN 10

9811564183

ISBN 13

9789811564185

Fish Development and Genetics

The Zebrafish and Medaka Models

By: Zhiyuan Gong,Vladimir Korzh

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Fish Development and Genetics

The Zebrafish and Medaka Models

By: Zhiyuan Gong,Vladimir Korzh

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Write a review

Solve jigsaw puzzle

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Page Count

700

Publisher

World Scientific

Published Date

ISBN 10

9812565760

ISBN 13

9789812565761

Book's by Zhiyuan Gong

Fish Development and Genetics

Fish Development and Genetics

Lifelong Machine Learning

Lifelong Machine Learning

Lifelong Machine Learning, Second Edition

Lifelong Machine Learning, Second Edition

Paper Tiger

Paper Tiger

Introduction to Graph Neural Networks

Introduction to Graph Neural Networks

Representation Learning for Natural Language Processing

Representation Learning for Natural Language Processing

Natural Gas Hydrate Management in Deepwater Gas Well

Natural Gas Hydrate Management in Deepwater Gas Well

Fish Development and Genetics

Fish Development and Genetics

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