tum-pbs / PhiFlowLinks
A differentiable PDE solving framework for machine learning
☆1,725Updated 3 weeks ago
Alternatives and similar repositories for PhiFlow
Users that are interested in PhiFlow are comparing it to the libraries listed below
Sorting:
- Computational Fluid Dynamics in JAX☆892Updated last week
- PDEBench: An Extensive Benchmark for Scientific Machine Learning☆990Updated 6 months ago
- A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…☆764Updated 3 months ago
- Differentiable Fluid Dynamics Package☆472Updated 3 weeks ago
- OSS library that implements deep learning methods for partial differential equations and much more☆455Updated last month
- Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond☆1,843Updated last month
- Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition☆1,203Updated 3 months ago
- Physics-Informed Neural networks for Advanced modeling☆585Updated last week
- All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.co…☆1,096Updated 5 months ago
- ☆491Updated 7 months ago
- A flexible framework for solving PDEs with modern spectral methods.☆617Updated 2 weeks ago
- ☆372Updated last month
- Learning nonlinear operators via DeepONet☆716Updated 3 years ago
- Using graph network to solve PDEs☆419Updated 5 months ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆471Updated last month
- XLB: Accelerated Lattice Boltzmann (XLB) for Physics-based ML☆412Updated last month
- Learning in infinite dimension with neural operators.☆3,074Updated this week
- A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods☆1,538Updated last year
- ☆1,041Updated last week
- Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML method…☆2,039Updated this week
- Differentiable Finite Element Method with JAX☆526Updated this week
- Lagrangian Neural Networks☆522Updated last month
- Python Dynamic Mode Decomposition☆1,058Updated last month
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,826Updated last month
- Code for our paper "Hamiltonian Neural Networks"☆491Updated 4 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆351Updated last year
- Python package for solving partial differential equations using finite differences.☆446Updated last week
- Framework providing pythonic APIs, algorithms and utilities to be used with PhysicsNeMo core to physics inform model training as well as …☆280Updated last week
- ☆369Updated 2 years ago
- PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks☆313Updated last year