Over the past few decades, the field of machine learning has made remarkable strides, surpassing human performance in tasks like voice and object recognition, as well as mastering various complex games. Despite these accomplishments, a critical challenge remains: the absence of general intelligence. Achieving artificial general intelligence (AGI) requires the development of learning agents that can continually adapt and learn throughout their existence, a concept known as lifelong learning...

3D deep learning is a rapidly evolving field that has the potential to transform various industries. This book provides a comprehensive overview of the current state-of-the-art in 3D deep learning, covering a wide range of research topics and applications. It collates the most recent research advances in 3D deep learning, including algorithms and applications, with a focus on efficient methods to tackle the key technical challenges in current 3D deep learning research and adoption, therefo...

Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficult...

This book provides a thorough exploration of the latest innovations in AI for general time series analysis, distribution shift and foundation models. It offers an in-depth look at cutting-edge techniques and methodologies, using advance algorithms that are transforming time series analysis across industries. The authors highlight the use AI models, particularly those based on deep learning, to study the sequence of data points collected at successive points in time. In the study of the use...

This thoroughly revised and expanded second edition of the Handbook of Markov Chain Monte Carlo reflects the dramatic evolution of MCMC methods since the publication of the first edition. With the addition of two new editors, Radu V. Craiu and Dootika Vats, this comprehensive reference now offers deeper insights into the theoretical foundations and cutting-edge developments that are reshaping the field.Key Features:Completely restruct...

This book provides a thorough exploration of the latest innovations in AI for general time series analysis, distribution shift, and foundation models. It offers an in-depth look at cutting-edge techniques and methodologies, using advanced algorithms that are transforming time series analysis across industries. The authors highlight the use of AI models, particularly those based on deep learning, to study the sequence of data points collected at successive points in time.In the stud...

Advances in Biosystems investigates the latest techniques for evaluating, detecting, measuring, and enhancing the functional bioactivities, chemical composition, and physicochemical characteristics of animal, plant, and environmental biosystems. This comprehensive, interdisciplinary handbook provides detailed explanations for tracking functional molecules during various biological processes, along with practical methodologies for both laboratory and industrial applications. Sections cover ...

Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning appl...

The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference. Despite the tremendous progress that has been made, statistical science is still a young discipline and continues to have several different and competing paths in its approaches and its foundations. While the emergence of competing approaches is a natural progression of any scientific discipline, differences in the fo...

This book constitutes the refereed proceedings of the 15th International Symposium on Advanced Parallel Processing Technologies, APPT 2023, held in Nanchang, China, during August 4–6, 2023.The 23 full papers and 1 short papers included in this book were carefully reviewed and selected from 49 submissions. They were organized in topical sections as follows: High Performance Computing and Parallelized Computing, Storage Systems and File Management, Networking and Cloud Computing, Com...

This book reviews cutting-edge developments in neural signalling processing (NSP), systematically introducing readers to various models and methods in the context of NSP.Neuronal Signal Processing is a comparatively new field in computer sciences and neuroscience, and is rapidly establishing itself as an important tool, one that offers an ideal opportunity to forge stronger links between experimentalists and computer scientists. This new signal-processing tool can be used in conjun...

This volume provides food researchers with advanced destructive and non-destructive techniques for measuring the chemical composition, functional bioactivities physicochemical changes, and explaining the functional mechanisms for facilitating the tracking of the functional molecules during the different industrial processes. Chapters guide readers through sample preparation emerging extraction technologies protocols analytical methodologies for phytochemicals profiling, multi way models in...