tonyshardlow / PICSPDE
Python codes for Introduction to Computational Stochastic PDE
☆43Updated 3 months ago
Alternatives and similar repositories for PICSPDE
Users that are interested in PICSPDE are comparing it to the libraries listed below
Sorting:
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆151Updated 5 years ago
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 3 years ago
- Companion code for "Solving Nonlinear and High-Dimensional Partial Differential Equations via Deep Learning" by A. Al-Aradi, A. Correia, …☆116Updated 5 years ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆177Updated 4 years ago
- Solving high-dimensional Partial Differential Equations with Deep Learning☆26Updated 5 years ago
- ☆41Updated 5 years ago
- Practicum on Supervised Learning in Function Spaces☆33Updated 3 years ago
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆25Updated 3 years ago
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆52Updated 2 years ago
- Code and files related to random side projects☆21Updated 3 years ago
- ☆177Updated last month
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆35Updated 3 years ago
- kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order☆72Updated 4 months ago
- Two Dimensional Fokker-Planck Solver using Matlab☆19Updated 5 years ago
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆39Updated 6 months ago
- ☆22Updated last month
- Numerical integration of Ito or Stratonovich SDEs☆168Updated 2 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆55Updated 2 years ago
- Quasi-Monte Carlo point generators, automatic transformations, and adaptive stopping criteria☆71Updated last week
- Discovers high dimensional models from 1D data using deep delay autoencoders☆34Updated 2 years ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆26Updated last year
- Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation☆12Updated 3 years ago
- ☆47Updated last year
- ☆104Updated last week
- Hidden physics models: Machine learning of nonlinear partial differential equations☆145Updated 5 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆56Updated 4 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆68Updated 4 years ago
- ☆12Updated 2 years ago
- Different methods of solving partial differential equations with neural networks☆17Updated 3 years ago
- Automatic Differentiation Library for Computational and Mathematical Engineering☆302Updated last year