[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Zhu et al., 2023 - Google Patents

Leveraging neural differential equations and adaptive delayed feedback to detect unstable periodic orbits based on irregularly sampled time series

Zhu et al., 2023

View PDF
Document ID
198572493521809197
Author
Zhu Q
Li X
Lin W
Publication year
Publication venue
Chaos: An Interdisciplinary Journal of Nonlinear Science

External Links

Snippet

Detecting unstable periodic orbits (UPOs) based solely on time series is an essential data- driven problem, attracting a great deal of attention and arousing numerous efforts, in nonlinear sciences. Previous efforts and their developed algorithms, though falling into a …
Continue reading at openreview.net (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/10Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation

Similar Documents

Publication Publication Date Title
Lu et al. Reservoir observers: Model-free inference of unmeasured variables in chaotic systems
Kröger et al. Analytical solution of the SIR-model for the temporal evolution of epidemics. Part A: time-independent reproduction factor
Saxe et al. On the information bottleneck theory of deep learning
Weigend Time series prediction: forecasting the future and understanding the past
Owolabi et al. Mathematical modeling and analysis of two-variable system with noninteger-order derivative
Pathak et al. Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data
Kapral Quantum dynamics in open quantum-classical systems
Lord et al. Geometric k-nearest neighbor estimation of entropy and mutual information
Mittal et al. Topological characterization and early detection of bifurcations and chaos in complex systems using persistent homology
Verzelli et al. Learn to synchronize, synchronize to learn
Maulik et al. Neural network representability of fully ionized plasma fluid model closures
Strnad et al. Deep reinforcement learning in World-Earth system models to discover sustainable management strategies
Schäfer et al. Control of stochastic quantum dynamics by differentiable programming
Fang et al. An end-to-end deep learning approach for extracting stochastic dynamical systems with α-stable Lévy noise
Zhu et al. Leveraging neural differential equations and adaptive delayed feedback to detect unstable periodic orbits based on irregularly sampled time series
Lu et al. Extracting stochastic governing laws by non-local Kramers–Moyal formulae
Naumova et al. Multi-penalty regularization with a component-wise penalization
Smith et al. Learning continuous chaotic attractors with a reservoir computer
Li et al. Extracting stochastic dynamical systems with α-stable Lévy noise from data
Bao et al. A score-based filter for nonlinear data assimilation
Chen et al. MAHGIC: a Model Adapter for the Halo–Galaxy Inter-Connection
Almazova et al. Analysis of chaotic dynamical systems with autoencoders
Youssry et al. Multi-axis control of a qubit in the presence of unknown non-Markovian quantum noise
Sartanpara et al. Solution of generalized fractional Jaulent–Miodek model with uncertain initial conditions
Klein et al. Derivation of Liouville-like equations for the n-state probability density of an open system with thermalized particle reservoirs and its link to molecular simulation