Alternatives and similar repositories for neuromancer

Users that are interested in neuromancer are comparing it to the libraries listed below

• dynamicslab / pysindy
  A package for the sparse identification of nonlinear dynamical systems from data
  ☆1,644Updated this week
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆374Updated 9 months ago
• mathLab / PINA
  Physics-Informed Neural networks for Advanced modeling
  ☆555Updated 3 weeks ago
• NeuroDiffGym / neurodiffeq
  A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…
  ☆756Updated last month
• boschresearch / torchphysics
  OSS library that implements deep learning methods for partial differential equations and much more
  ☆450Updated last month
• kpchamp / SindyAutoencoders
  ☆366Updated 3 years ago
• PyDMD / PyDMD
  Python Dynamic Mode Decomposition
  ☆1,024Updated 3 weeks ago
• patrick-kidger / diffrax
  Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
  ☆1,734Updated 2 weeks ago
• pdebench / PDEBench
  PDEBench: An Extensive Benchmark for Scientific Machine Learning
  ☆954Updated 3 months ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆424Updated last year
• tum-pbs / PhiFlow
  A differentiable PDE solving framework for machine learning
  ☆1,662Updated 3 weeks ago
• PredictiveIntelligenceLab / jaxpi
  ☆336Updated 4 months ago
• benmoseley / harmonic-oscillator-pinn
  Code accompanying my blog post: So, what is a physics-informed neural network?
  ☆620Updated 3 years ago
• MilesCranmer / lagrangian_nns
  Lagrangian Neural Networks
  ☆508Updated last year
• benmoseley / FBPINNs
  Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…
  ☆439Updated 2 months ago
• google / jax-cfd
  Computational Fluid Dynamics in JAX
  ☆869Updated 4 months ago
• Ceyron / machine-learning-and-simulation
  All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.co…
  ☆1,046Updated 2 months ago
• greydanus / hamiltonian-nn
  Code for our paper "Hamiltonian Neural Networks"
  ☆479Updated 4 years ago
• lululxvi / deeponet
  Learning nonlinear operators via DeepONet
  ☆691Updated 3 years ago
• GilpinLab / dysts
  Hundreds of strange attractors
  ☆487Updated last week
• jayroxis / PINNs
  PyTorch Implementation of Physics-informed Neural Networks
  ☆652Updated last year
• Koopman-Laboratory / KoopmanLab
  A library for Koopman Neural Operator with Pytorch.
  ☆302Updated 10 months ago
• mroberto166 / CAMLab-DLSCTutorials
  ☆204Updated last year
• Zymrael / awesome-neural-ode
  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…
  ☆1,465Updated 11 months ago
• NVIDIA / physicsnemo
  Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML method…
  ☆1,793Updated this week
• rezaakb / pinns-torch
  PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.
  ☆619Updated 2 months ago
• jdtoscano94 / Learning-Scientific_Machine_Learning_Residual_Based_Attention_PINNs_PIKANs_DeepONets
  Physics Informed Machine Learning Tutorials (Pytorch and Jax)
  ☆580Updated 6 months ago
• SMTorg / smt
  Surrogate Modeling Toolbox
  ☆794Updated last week
• dynamicslab / databook_python
  IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Sy…
  ☆923Updated last year
• dynamicslab / SINDy-PI
  SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
  ☆152Updated 4 years ago