pnnl / neuromancer
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
☆1,006Updated this week
Alternatives and similar repositories for neuromancer:
Users that are interested in neuromancer are comparing it to the libraries listed below
- ☆423Updated last month
- A package for computing data-driven approximations to the Koopman operator.☆327Updated 2 months ago
- A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…☆719Updated 6 months ago
- Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML method…☆1,162Updated this week
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,524Updated this week
- ☆251Updated 2 months ago
- Physics-Informed Neural networks for Advanced modeling☆423Updated this week
- Python Dynamic Mode Decomposition☆919Updated 3 weeks ago
- PDEBench: An Extensive Benchmark for Scientific Machine Learning☆822Updated this week
- Hundreds of strange attractors☆435Updated this week
- A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods☆1,429Updated 8 months ago
- A package for the sparse identification of nonlinear dynamical systems from data☆1,508Updated this week
- A differentiable PDE solving framework for machine learning☆1,540Updated this week
- neural networks to learn Koopman eigenfunctions☆387Updated 10 months ago
- ☆344Updated 3 years ago
- Lagrangian Neural Networks☆475Updated 7 months ago
- Code accompanying my blog post: So, what is a physics-informed neural network?☆576Updated 2 years ago
- Code for our paper "Hamiltonian Neural Networks"☆441Updated 3 years ago
- ☆398Updated 11 months ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆347Updated last month
- Using graph network to solve PDEs☆370Updated last year
- PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.☆92Updated 8 months ago
- Welcome to the Physics-based Deep Learning Book (v0.2)☆1,035Updated last month
- PyTorch Implementation of Physics-informed Neural Networks☆570Updated 8 months ago
- ☆186Updated 6 months ago
- Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation☆778Updated 3 months ago
- Physics Informed Machine Learning Tutorials (Pytorch and Jax)☆495Updated 2 months ago
- Learning nonlinear operators via DeepONet☆579Updated 2 years ago
- IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.☆214Updated 3 months ago
- Computational Fluid Dynamics in JAX☆784Updated 5 months ago