Empowering Deep Learning With Graphs
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Empowering Deep Learning With Graphs
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Author : Jiaxuan You (Machine learning researcher)
language : en
Publisher:
Release Date : 2021
Empowering Deep Learning With Graphs written by Jiaxuan You (Machine learning researcher) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Deep learning has reshaped the research and applications in artificial intelligence. Modern deep learning models are primarily designed for regular-structured data, such as sequences and images. These models are built for tasks that take these regular-structured data as the input (e.g., classification, regression), as the output (e.g., generation), or as the structural prior (e.g., neural architecture design). However, not all forms of data are regular-structured. One notable example is graph-structured data, a general and powerful data structure that represents entities and their relationships in a succinct form. While graph-structured data is ubiquitous throughout the natural and social sciences, its discrete and non-i.i.d. nature brings unique challenges to modern deep learning models. In this thesis, we aim to empower deep learning with graph-structured data, by facilitating deep learning models to take graphs as the input, the output, and the prior. My research in these three directions has opened new frontiers for deep learning research: (1) Learning from graphs with deep learning. We develop expressive and effective deep learning methods that can take graphs as the input, which promotes the learning and understanding of graphs. (2) Generation of graphs with deep learning. We formulate the generation process of graphs using deep learning models, which advances the discovery and design of graphs. (3) Graph as the prior for deep learning. We discover that graph structure can serve as a powerful prior for neural architectures and machine learning tasks, which opens a new direction for the design and understanding of deep learning. Finally, we discuss the wide applications of the above-mentioned techniques, including recommender systems, drug discovery, neural architecture design, and missing data imputation.
Computer Vision Eccv 2024
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Author : Aleš Leonardis
language : en
Publisher: Springer Nature
Release Date : 2024-11-16
Computer Vision Eccv 2024 written by Aleš Leonardis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-16 with Computers categories.
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation.
Graph Neural Networks In Action
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Author : Keita Broadwater
language : en
Publisher: Simon and Schuster
Release Date : 2025-04-15
Graph Neural Networks In Action written by Keita Broadwater and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Computers categories.
Graph Neural Networks in Action is a great guide about how to build cutting-edge graph neural networks and powerful deep learning models for recommendation engines, molecular modeling, and more. Ideal for Python programmers, you will dive into graph neural networks perfect for node prediction, link prediction, and graph classification.
Scaling Graph Learning For The Enterprise
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Author : Ahmed Menshawy
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-08-06
Scaling Graph Learning For The Enterprise written by Ahmed Menshawy and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-06 with Computers categories.
Tackle the core challenges related to enterprise-ready graph representation and learning. With this hands-on guide, applied data scientists, machine learning engineers, and practitioners will learn how to build an E2E graph learning pipeline. You'll explore core challenges at each pipeline stage, from data acquisition and representation to real-time inference and feedback loop retraining. Drawing on their experience building scalable and production-ready graph learning pipelines, the authors take you through the process of building robust graph learning systems in a world of dynamic and evolving graphs. Understand the importance of graph learning for boosting enterprise-grade applications Navigate the challenges surrounding the development and deployment of enterprise-ready graph learning and inference pipelines Use traditional and advanced graph learning techniques to tackle graph use cases Use and contribute to PyGraf, an open source graph learning library, to help embed best practices while building graph applications Design and implement a graph learning algorithm using publicly available and syntactic data Apply privacy-preserving techniques to the graph learning process
Leveraging Large Language Models For Quantum Aware Cybersecurity
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Author : Zangana, Hewa Majeed
language : en
Publisher: IGI Global
Release Date : 2024-12-26
Leveraging Large Language Models For Quantum Aware Cybersecurity written by Zangana, Hewa Majeed and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-26 with Computers categories.
As the digital landscape evolves, the growing threat of cyberattacks has prompted the need for more advanced security measures. One of the most promising developments in cybersecurity is the integration of large language models (LLMs) with quantum-aware systems. These AI-powered models, capable of processing data and recognizing complex patterns, play a pivotal role in identifying vulnerabilities, predicting threats, and enhancing the resilience of security infrastructures. In quantum computing, LLMs offer new opportunities to stay ahead of cyber threats by simulating attack strategies and developing adaptive defense mechanisms. By harnessing the power of these tools, cybersecurity professionals can address current challenges while preparing for an era of quantum-enabled cyber threats. Leveraging Large Language Models for Quantum-Aware Cybersecurity explores the convergence of LLMs, cybersecurity, and quantum computing, providing an in-depth analysis of how these fields are being integrated to tackle emerging challenges in the digital security landscape. It covers foundational concepts, cutting-edge research, and practical applications, demonstrating how LLMs can be leveraged alongside quantum technologies to enhance threat detection, automate incident response, and build quantum-resilient security frameworks. This book covers topics such as artificial intelligence, computer engineering, natural language processing, and is a useful resource for computer engineers, security professionals, scientists, academicians, and researchers.
100 Best Generative Ai Tools
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Author : Prabhu TL
language : en
Publisher: NestFame Creations Pvt Ltd.
Release Date :
100 Best Generative Ai Tools written by Prabhu TL and has been published by NestFame Creations Pvt Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
In the era of groundbreaking technological advancements, the book "100 Best Generative AI Tools" is your passport to an exhilarating expedition through the realms of creativity, imagination, and innovation. This captivating guide unveils a curated selection of the most remarkable and transformative generative AI tools that are reshaping the landscape of human ingenuity across a multitude of industries. Unlocking the Power of Generative AI: Imagine a world where machines possess the remarkable ability to generate art, music, literature, and even entire virtual realities. In "100 Best Generative AI Tools," you'll venture into this awe-inspiring realm, where algorithms fuse with creativity to produce captivating and unprecedented results. Whether you're an artist, a musician, a writer, or an innovator, this book empowers you to harness the potential of generative AI to amplify your creative endeavors. A Treasury of Creative Possibilities: This book serves as a treasure trove of innovative generative AI tools, meticulously curated to offer a diverse and comprehensive range of applications. From producing mesmerizing visual masterpieces to composing evocative musical compositions, and from crafting compelling narratives to designing immersive virtual landscapes—each tool is a gateway to limitless creative possibilities. Behind the Algorithmic Curtain: Delve deeper into the intricate workings of these generative AI tools as you unravel the science behind the algorithms. "100 Best Generative AI Tools" deciphers complex concepts into accessible insights, making it a captivating read for both enthusiasts and those new to the field. Explore how neural networks, deep learning, and cutting-edge technology collaborate harmoniously to produce works of art that rival human creativity. Crossing Boundaries and Industries: The impact of generative AI knows no bounds, transcending industries and reshaping the way we perceive creativity. Whether you're a fashion designer pushing the boundaries of design, a game developer crafting immersive digital experiences, or a scientist generating data-driven insights, the tools showcased in this book will spark your imagination and transform your approach to innovation. Empowering Creative Minds: "100 Best Generative AI Tools" goes beyond mere description; it provides you with the tools and knowledge to unleash your creative potential. Whether you're a curious novice or an experienced artist, this book equips you with the resources to embark on a journey of experimentation, discovery, and artistic evolution. Shape the Future of Creativity: As you delve into the pages of "100 Best Generative AI Tools," you become part of a transformative movement that is redefining the boundaries of human creativity. With these tools at your fingertips, you have the power to amplify your artistic voice, challenge traditional norms, and craft a future where the fusion of AI and imagination knows no limits. Join the Creative Revolution: Are you ready to join the ranks of visionaries who are seamlessly blending art, technology, and innovation? "100 Best Generative AI Tools" is your guide to embracing the future, where the canvas of creativity knows no boundaries and the brush strokes of imagination are powered by algorithms. Step into a world where your creative potential knows no limits, and let the journey of innovation begin.
Leveraging Emerging Technologies And Analytics For Empowering Humanity Vol 1
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Author : D P Goyal
language : en
Publisher: Springer Nature
Release Date : 2025-05-15
Leveraging Emerging Technologies And Analytics For Empowering Humanity Vol 1 written by D P Goyal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-15 with Computers categories.
This book provides a platform for interdisciplinary discussions on leveraging emerging technologies and analytics to empower humanity, fostering collaboration between experts in AI and analytics, sustainability, different areas of management, and IT. As the world grapples with complex challenges, from climate change to economic inequality, this first volume of a two-volume proceedings series is a crucial resource for fostering collaboration and exploring untapped potential of emerging technologies. By harnessing the power of AI, blockchain, IoT, and big data, the chapters address critical global challenges towards improving quality of life and promoting inclusive and sustainable development, while keeping in mind ethical implications, and their impact on social justice. The volume will be of use to thought leaders, researchers, innovators, and policymakers from around the globe who are interested in knowing more on how cutting-edge technologies can be harnessed for the greater good of society.
Libraries In Transformation
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Author : Phayung Meesad
language : en
Publisher: Springer Nature
Release Date : 2024-11-07
Libraries In Transformation written by Phayung Meesad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-07 with Computers categories.
This book discovers how libraries evolved in the digital age with “Libraries in Transformation: Navigating to AI-powered Libraries.” This insightful book explores the profound shifts within libraries due to the integration of advanced technologies such as artificial intelligence (AI) and the Internet of Things (IoT). Providing a comprehensive roadmap, this book guides libraries in adapting and thriving while maintaining their core mission of providing universal access to knowledge and fostering community engagement.
Pattern Recognition And Computer Vision
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Author : Qingshan Liu
language : en
Publisher: Springer Nature
Release Date : 2023-12-23
Pattern Recognition And Computer Vision written by Qingshan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-23 with Computers categories.
The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis.
Oneflow For Parallel And Distributed Deep Learning Systems
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Author : William Smith
language : en
Publisher: HiTeX Press
Release Date : 2025-07-12
Oneflow For Parallel And Distributed Deep Learning Systems written by William Smith and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-12 with Computers categories.
"OneFlow for Parallel and Distributed Deep Learning Systems" In a rapidly evolving landscape of machine learning infrastructure, "OneFlow for Parallel and Distributed Deep Learning Systems" provides a comprehensive and authoritative exploration of the OneFlow framework as a cornerstone for large-scale deep learning. Through an expert survey of distributed learning architectures, the book delves into OneFlow’s core system principles, innovative design philosophies, and its architectural evolution in comparison to platforms like TensorFlow, PyTorch, Horovod, and MXNet. It thoroughly addresses the foundational challenges inherent in scaling neural network training across cloud, cluster, and high-performance computing environments, presenting both the formal models and practical paradigms that underpin efficient parallelism. The text offers an in-depth technical journey into every critical component of the OneFlow architecture—from scheduling, resource management, and data pipelines to elasticity and fault recovery. Readers will find rigorous coverage of parallelism techniques, encompassing data, model, and pipeline parallelism, hybrid strategies, as well as device placement and load balancing for optimal efficiency. With advanced sections dedicated to state-of-the-art communication protocols, synchronization models, and hardware-aware optimizations, the book equips practitioners to maximize throughput and resilience in both research and production environments. Beyond architectural mastery, this book bridges theory with practice through hands-on guidance in cluster deployment, monitoring, security, debugging, and extensibility for heterogeneous backends. Case studies illuminate end-to-end applications in vision, NLP, and multimodal domains, while sections on federated learning, green AI, and compiler integration reveal emerging frontiers. Culminating with community-driven innovations and lessons from real-world deployments, this volume is an essential resource for engineers, researchers, and technical leaders seeking to harness the full potential of scalable, distributed deep learning with OneFlow.