Recent Trends in Modelling the Time Series by Mansura Habiba (.ePUB)+
File Size: 21.5 MB
Recent Trends in Modelling the Continuous Time Series Using Deep Learning by Mansura Habiba, Barak A. Pearlmutter, Mehrdad Maleki
Requirements: .ePUB, .PDF reader, 21.5 MB | True PDF, True EPUB
Overview: This book presents the first unified, practical framework for continuous-time series analysis using state-of-the-art neural architectures. Moving beyond traditional discrete-time methods, it directly addresses real-world challenges such as irregular sampling, asynchronous observations, and hidden system dynamics through Neural ODEs, SDEs, and CDEs. Covering both foundational and advanced models — RNNs, Transformers, graph networks, and emerging quantum-hybrid approaches — the book bridges classical time-series theory with modern Deep Learning. It emphasizes probabilistic forecasting, uncertainty quantification, and cutting-edge generative techniques, including diffusion models and VAEs, equipping readers with tools for robust, interpretable predictions. Throughout this book, we aim to unify multiple research trajectories—Deep Learning, stochastic modeling, and quantum computing—into a coherent framework for understanding the temporal continuum. Each chapter can be read independently but is designed to build toward a larger epistemic goal: to establish continuous-time modeling as a foundational pillar for the next generation of intelligent systems.
Genre: Non-Fiction > Tech & Devices
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