-
Kuramoto-Sivashinsky Equation
The Kuramoto-Sivashinsky equation is a model for spatiotemporal chaos. The Kuramoto-Sivashinsky equation is expressed as: yt = −yyx − yxx − yxxxx -
Neural Certificates for Safe Control Policies
This paper develops an approach to learn a policy of a dynamical system that is guaranteed to be both provably safe and goal-reaching. -
Lorenz System
The Lorenz system is a well-known nonlinear dynamical system to model convective hydrodynamic flows. The consequence of chaos is that, under certain parameterizations, the... -
Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Pre...
A dataset of synthetic dynamical systems, including the Lorenz system and a generalized cartpole problem, used to evaluate the performance of the Neural Dynamical Systems (NDS)... -
lfads-torch: A modular and extensible implementation of latent factor analysi...
Latent factor analysis via dynamical systems (LFADS) is an RNN-based variational sequential autoencoder that achieves state-of-the-art performance in denoising high-dimensional... -
Unknown Dynamical Systems
The dataset is used to test the proposed generalized residue network (gResNet) framework for learning unknown governing equations from observational data. -
RADAR (Research Data Repository)
Imported
Experimental data for the paper "knowledge-guided learning of temporal dynami...
Abstract: These are experimental data for the paper: Pawel Bielski, Aleksandr Eismont, Jakob Bach, Florian Leiser, Dustin Kottonau, and Klemens Böhm. 2024. Knowledge-Guided... -
Leibniz University Hannover
Imported
Gaussian Processes with Noisy Regression Inputs for Dynamical Systems
We here provide the code related to our recent paper "Gaussian Processes with Noisy Regression Inputs for Dynamical Systems". To run the code, execute the 'offline_phase.mat' or...
