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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Informatik & EDV Informatik Recent Trends in Modelling the Continuous Time Series Using Deep Learning
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Recent Trends in Modelling the Continuous Time Series Using Deep Learning
Mansura Habiba, Barak Pearlmutter, Mehrdad Maleki (Gebundene Ausgabe, Englisch)
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Beschreibung
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. Recent Trends in Modelling the Continuous Time Series using Deep Learning tackles core issues such as long-range dependencies, multivariate interactions, dimensionality reduction, and spatiotemporal coherence, while providing structured evaluation frameworks and benchmarking protocols tailored to continuous-time settings. Through rich case studies in healthcare (EHR analytics, wearable monitoring), finance (volatility forecasting, high-frequency trading), and IoT systems (sensor fusion, predictive maintenance), the book demonstrates how continuous-time models enable personalized insights, constraint-aware learning, and more reliable decision-making. Designed for researchers, engineers, and practitioners, this book is a definitive resource for applying continuous-time neural methods to complex, real-world environments. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
03.06.2026
Sprache
Englisch
EAN
9783032180216
Herausgeber
Springer International Publishing
Sonderedition
Nein
Autor
Mansura Habiba, Barak Pearlmutter, Mehrdad Maleki
Seitenanzahl
269
Einbandart
Gebundene Ausgabe
Schlagwörter
Continuous Time Series Analysis, Neural Ordinary Differential Equations (Neural ODEs), Neural Stochastic Differential Equations (Neural SDEs), Time Series Forecasting, Multivariate Time Series, Generative Models for Time series, Probabilistic Forecasting, Transformer Architecture, Graph Neural Networks, Attention Mechanisms, Quantum-Hybrid Neural Networks
Thema-Inhalt
UYQ - Künstliche Intelligenz
PBT - Wahrscheinlichkeitsrechnung und Statistik
UYQM - Maschinelles Lernen
PBWH - Mathematische Modellierung
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Nature Customer Service Center GmbH, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com
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