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Physics-Informed Neural Operator (PINO) dataset
The dataset used in the paper for training and testing the Physics-Informed Neural Operator (PINO) model. -
SNAPE: Theory-guided learning of PDEs from data
The dataset used in this paper is a collection of measured responses of various physical processes, including the wave equation, chaotic response of forced Duffing oscillator,... -
2D KS System with Spatial Inhomogeneities
The dataset used in the paper is a 2D KS system with spatial inhomogeneities. The system is simulated on a grid of size 256x256. -
2D KS System
The dataset used in the paper is a 2D KS system with periodic boundary conditions. The system is simulated on a grid of size 256x256. -
Sliding-Window Approach for PDEs
The dataset used in the paper is a sliding-window approach with an extent of ℓ = 1 and a stride of s = 2. The dataset is a 256x256 grid with 512 nodes, and the state function is... -
Predictions based on pixel data: Insights from PDEs and finite differences
The dataset used in this paper is a set of space-time observations of PDE solutions, generated using finite element simulations.