PF-PINNs: physics-informed neural networks framework for solving coupled Allen-Cahn and Cahn-Hilliard phase field equations
☆29Feb 18, 2025Updated last year
Alternatives and similar repositories for PF-PINNs
Users that are interested in PF-PINNs are comparing it to the libraries listed below
Sorting:
- PINNs-MPF is a comprehensive framework designed for simulating interface dynamics using Physics-Informed Neural Networks (PINNs). Leverag…☆20Apr 11, 2025Updated 10 months ago
- Prediction of Fluid Flow in Porous Media by Sparse Observations and Physics-Informed PointNet☆14Aug 24, 2024Updated last year
- Code for paper "Beyond Closure Models: Learning Chaotic Systems via Physics-Informed Neural Operators".☆14Dec 24, 2025Updated 2 months ago
- Qi ZHANG's simulation code (very preliminary and there are a lot of aspects to improve)☆15Jan 23, 2026Updated last month
- The repository contains implementations of examples provided in the literature on energy minimization based approach to Physics Informed …☆11Apr 8, 2020Updated 5 years ago
- ☆10Mar 31, 2021Updated 4 years ago
- Tensoflow 2 implementation of physics informed deep learning.☆27Sep 12, 2020Updated 5 years ago
- Benchmark problems of GPU computing of phase-field models☆13Oct 26, 2022Updated 3 years ago
- Rheological Universal Differential Equations: scientific machine learning for modeling complex fluids☆19Dec 23, 2022Updated 3 years ago
- XPINN code written in TensorFlow 2☆28Feb 1, 2023Updated 3 years ago
- ☆33Jan 10, 2025Updated last year
- Use SINDY algorithm to discover a dynamical system from coronavirus data☆13Apr 9, 2024Updated last year
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Apr 10, 2021Updated 4 years ago
- ☆13Apr 5, 2024Updated last year
- ☆41Mar 4, 2025Updated last year
- ☆14Jan 22, 2022Updated 4 years ago
- ☆17Aug 13, 2024Updated last year
- Spectral methods in matlab☆12Mar 27, 2025Updated 11 months ago
- Code for the paper "Deep learning of thermodynamics-aware reduced-order models from data" published in Computer Methods in Applied Mechan…☆14Aug 18, 2023Updated 2 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Nov 3, 2021Updated 4 years ago
- Code for the paper "Structure-preserving neural networks" published in Journal of Computational Physics (JCP).☆19Aug 18, 2023Updated 2 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆39Jul 12, 2023Updated 2 years ago
- ☆17Nov 26, 2024Updated last year
- Multi-head attention network for airfoil flow field prediction☆17Sep 13, 2022Updated 3 years ago
- Physics-informed neural networks☆16Nov 26, 2020Updated 5 years ago
- ☆12Aug 22, 2025Updated 6 months ago
- ☆18May 25, 2024Updated last year
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Mar 25, 2023Updated 2 years ago
- ☆16Dec 13, 2022Updated 3 years ago
- The phase field code of simulation about reversible domain switch phenomena in ferroelectric material.☆26Nov 23, 2020Updated 5 years ago
- This is the official implementation of "Deep Fuzzy Physics-Informed Neural Networks for Forward and Inverse PDE Problems" (Neural Network…☆27Oct 14, 2025Updated 4 months ago
- ☆23Jul 25, 2024Updated last year
- FastVPINNs - A tensor-driven acceleration of VPINNs for complex geometries☆47Feb 2, 2025Updated last year
- ☆24Dec 21, 2023Updated 2 years ago
- A novel DeepONet architecture that is specifically designed for generating predictions on different 3D geometries discretized by differen…☆24Jul 25, 2024Updated last year
- ☆28Oct 21, 2024Updated last year
- Solving High Frequency and Multi-Scale PDEs with Gaussian Processes (ICLR 2024)☆26Jun 7, 2024Updated last year
- ☆26Jul 7, 2022Updated 3 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆25May 30, 2023Updated 2 years ago