pnnl / neuromancerLinks
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
☆1,210Updated 2 weeks ago
Alternatives and similar repositories for neuromancer
Users that are interested in neuromancer are comparing it to the libraries listed below
Sorting:
- A package for the sparse identification of nonlinear dynamical systems from data☆1,683Updated last week
- A package for computing data-driven approximations to the Koopman operator.☆387Updated 11 months ago
- Physics-Informed Neural networks for Advanced modeling☆582Updated this week
- OSS library that implements deep learning methods for partial differential equations and much more☆454Updated 3 weeks ago
- ☆373Updated 4 years ago
- Lagrangian Neural Networks☆517Updated last month
- A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…☆766Updated 3 months ago
- Python Dynamic Mode Decomposition☆1,055Updated 3 weeks ago
- ☆365Updated last month
- neural networks to learn Koopman eigenfunctions☆439Updated last year
- PDEBench: An Extensive Benchmark for Scientific Machine Learning☆982Updated 5 months ago
- Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/☆1,810Updated 3 weeks ago
- A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods☆1,534Updated last year
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆465Updated 2 weeks ago
- Code for our paper "Hamiltonian Neural Networks"☆486Updated 4 years ago
- A differentiable PDE solving framework for machine learning☆1,722Updated last week
- All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.co…☆1,082Updated 4 months ago
- Code accompanying my blog post: So, what is a physics-informed neural network?☆649Updated 3 years ago
- Hundreds of strange attractors☆496Updated last month
- A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…☆1,486Updated last year
- SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics☆153Updated 4 years ago
- A toolkit with data-driven pipelines for physics-informed machine learning.☆189Updated last month
- Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems☆146Updated 3 months ago
- Learning nonlinear operators via DeepONet☆703Updated 3 years ago
- Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML method…☆1,971Updated this week
- Code for "SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning" by Zolman et al.☆140Updated last month
- ☆210Updated last year
- Physics Informed Machine Learning Tutorials (Pytorch and Jax)☆595Updated 8 months ago
- PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.☆145Updated last year
- IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Sy…☆944Updated last year