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Discovery of Dynamics via Deep Learning
The dataset used in the paper is a collection of time series data from a dynamical system, which is used to test the performance of the network-based LMMs for discovering... -
Kuramoto-Sivashinsky Equation
The Kuramoto-Sivashinsky equation is a model for spatiotemporal chaos. The Kuramoto-Sivashinsky equation is expressed as: yt = −yyx − yxx − yxxxx -
State Space Representations of Deep Neural Networks
This paper deals with neural networks as dynamical systems governed by finite difference equations. It shows that the introduction of k-many skip connections into network... -
Damped Harmonic Oscillator with Displacement-Dependent Damping and Restoring ...
The dataset consists of a damped harmonic oscillator with a displacement-dependent damping and restoring force, where the governing equation is given by¨y = −c1 ˙y − k1 y + 0.1t... -
Damped Harmonic Oscillator with Time-Dependent Forcing
The dataset consists of a damped harmonic oscillator with a time-dependent forcing function, where the governing equation is given by m¨y = −c ˙y − ky + F(t). -
Reaction-Diffusion PDE
The dataset used in this paper is a 1-dimensional reaction-diffusion equation. -
Reaction-Diffusion PDE and Van der Pol Oscillator
The dataset used in this paper is a 2-dimensional reaction-diffusion equation, and a 2-dimensional Van der Pol oscillator. -
Lorenz-63 System
The dataset used in this paper is a collection of time series data from various dynamical systems, including the harmonic oscillator, Duffing system, Van der Pol oscillator, and... -
Harmonic Oscillator, Duffing System, Van der Pol Oscillator, Lorenz-63 System
The dataset used in this paper is a collection of time series data from various dynamical systems, including the harmonic oscillator, Duffing system, Van der Pol oscillator, and... -
UCI Regression Datasets
The dataset used in the paper is the UCI Regression Datasets, which are a standard benchmark for evaluating conditional density estimators.
