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4D-ODE dataset
The dataset used for the 4D-ODE example, containing 10,000 data points with 6 input features and 4 output features. -
1D-ODE dataset
The dataset used for the 1D-ODE example, containing 200 data points with 2 input features and 2 output features. -
One-Shot Transfer Learning of Physics-Informed Neural Networks
The dataset used in this paper for one-shot transfer learning of physics-informed neural networks. -
Monte Carlo Physics-Informed Neural Networks
A deep learning approach for solving forward and inverse problems involving fractional partial differential equations. -
Allen-Cahn and Helmholtz datasets
The dataset used in this paper for the 1D Allen-Cahn equation and the 2D Helmholtz equation. -
Functional Priors and Posteriors from Data and Physics
The dataset used in this paper is a collection of historical data for learning functional priors and posteriors from data and physics. -
Navier-Stokes Equations Dataset
The dataset used in this paper for the Navier-Stokes equations problem. -
Heat Equation Dataset
The dataset used in this paper for the heat equation problem. -
Design of Turing Systems with Physics-Informed Neural Networks
Reaction-diffusion (Turing) systems are fundamental to the formation of spatial patterns in nature and engineering. These systems are governed by a set of non-linear partial... -
PI-VAE dataset
The dataset used in this paper is a collection of stochastic processes, including k(x, ω), f (x, ω), and b(x, ω), which are used to solve stochastic differential equations... -
PIANO dataset
The dataset used in this paper is a collection of PDE series with varying physical mechanisms.
