Alternatives and similar repositories for neuromancer

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

• boschresearch / torchphysics
  OSS library that implements deep learning methods for partial differential equations and much more
  ☆440Updated last month
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆361Updated 7 months ago
• pdebench / PDEBench
  PDEBench: An Extensive Benchmark for Scientific Machine Learning
  ☆919Updated last month
• mathLab / PINA
  Physics-Informed Neural networks for Advanced modeling
  ☆515Updated last week
• MilesCranmer / lagrangian_nns
  Lagrangian Neural Networks
  ☆501Updated 11 months ago
• NeuroDiffGym / neurodiffeq
  A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…
  ☆745Updated 4 months ago
• dynamicslab / pysindy
  A package for the sparse identification of nonlinear dynamical systems from data
  ☆1,596Updated last week
• greydanus / hamiltonian-nn
  Code for our paper "Hamiltonian Neural Networks"
  ☆474Updated 4 years ago
• PredictiveIntelligenceLab / jaxpi
  ☆313Updated last month
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆417Updated last year
• kpchamp / SindyAutoencoders
  ☆357Updated 3 years ago
• PyDMD / PyDMD
  Python Dynamic Mode Decomposition
  ☆1,003Updated 3 weeks ago
• patrick-kidger / diffrax
  Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
  ☆1,675Updated this week
• bitzhangcy / Neural-PDE-Solver
  ☆955Updated last week
• lululxvi / deeponet
  Learning nonlinear operators via DeepONet
  ☆660Updated 3 years ago
• benmoseley / FBPINNs
  Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…
  ☆422Updated last month
• NVIDIA / physicsnemo
  Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML method…
  ☆1,615Updated this week
• DiffEqML / torchdyn
  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
  ☆1,504Updated last year
• Koopman-Laboratory / KoopmanLab
  A library for Koopman Neural Operator with Pytorch.
  ☆290Updated 8 months ago
• tum-pbs / PhiFlow
  A differentiable PDE solving framework for machine learning
  ☆1,626Updated 2 months ago
• jdtoscano94 / Learning-Scientific_Machine_Learning_Residual_Based_Attention_PINNs_PIKANs_DeepONets
  Physics Informed Machine Learning Tutorials (Pytorch and Jax)
  ☆561Updated 4 months ago
• Zymrael / awesome-neural-ode
  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…
  ☆1,439Updated 9 months ago
• omniscientoctopus / Physics-Informed-Neural-Networks
  Investigating PINNs
  ☆606Updated 3 years ago
• neuraloperator / physics_informed
  ☆460Updated 2 months ago
• tum-pbs / pbdl-book
  Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition
  ☆1,118Updated last week
• idrl-lab / idrlnet
  IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
  ☆230Updated 8 months ago
• neuraloperator / graph-pde
  Using graph network to solve PDEs
  ☆397Updated 3 weeks ago
• neuraloperator / neuraloperator
  Learning in infinite dimension with neural operators.
  ☆2,722Updated last week
• jayroxis / PINNs
  PyTorch Implementation of Physics-informed Neural Networks
  ☆631Updated last year
• GilpinLab / dysts
  Hundreds of strange attractors
  ☆476Updated 3 weeks ago