10 datasets found

The dataset used in this paper is a collection of neural abstractions for dynamical models. The dataset consists of neural networks with different activation functions...

The dataset used in this paper is a collection of simulated trajectories of physical systems, including n-pendulum, n-spring, 4-body gravitational system, and rigid-body system.

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...

The Kuramoto-Sivashinsky equation is a model for spatiotemporal chaos. The Kuramoto-Sivashinsky equation is expressed as: yt = −yyx − yxx − yxxxx

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...

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...

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).

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...

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...

The dataset used in the paper is the UCI Regression Datasets, which are a standard benchmark for evaluating conditional density estimators.