Alternatives and similar repositories for symbolic_deep_learning

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

• SJ001 / AI-Feynman
  ☆716Updated last year
• dso-org / deep-symbolic-optimization
  A deep learning framework for symbolic optimization.
  ☆682Updated 9 months ago
• MilesCranmer / lagrangian_nns
  Lagrangian Neural Networks
  ☆517Updated last month
• DiffEqML / torchdyn
  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
  ☆1,531Updated last year
• greydanus / hamiltonian-nn
  Code for our paper "Hamiltonian Neural Networks"
  ☆486Updated 4 years ago
• facebookresearch / SymbolicMathematics
  Deep Learning for Symbolic Mathematics
  ☆548Updated 4 years ago
• cavalab / srbench
  A living benchmark framework for symbolic regression
  ☆274Updated last week
• MilesCranmer / PySR
  High-Performance Symbolic Regression in Python and Julia
  ☆3,148Updated this week
• kpchamp / SindyAutoencoders
  ☆371Updated 4 years ago
• patrick-kidger / NeuralCDE
  Code for "Neural Controlled Differential Equations for Irregular Time Series" (Neurips 2020 Spotlight)
  ☆670Updated 3 years ago
• patrick-kidger / diffrax
  Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
  ☆1,800Updated 3 weeks ago
• google-deepmind / jraph
  A Graph Neural Network Library in Jax
  ☆1,450Updated last year
• NeuroDiffGym / neurodiffeq
  A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…
  ☆766Updated 2 months ago
• google-research / torchsde
  Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
  ☆1,678Updated 9 months ago
• EmilienDupont / augmented-neural-odes
  Pytorch implementation of Augmented Neural ODEs
  ☆552Updated 2 years ago
• SymposiumOrganization / NeuralSymbolicRegressionThatScales
  Source code and Dataset creation for the paper "Neural Symbolic Regression That Scales"
  ☆102Updated last month
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆459Updated last year
• Zymrael / awesome-neural-ode
  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…
  ☆1,486Updated last year
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆284Updated 3 years ago
• boschresearch / torchphysics
  OSS library that implements deep learning methods for partial differential equations and much more
  ☆453Updated 3 weeks ago
• titu1994 / tfdiffeq
  Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
  ☆223Updated 5 years ago
• facebookresearch / symbolicregression
  SR based on LLMs.
  ☆116Updated 2 years ago
• secondmind-labs / trieste
  A Bayesian optimization toolbox built on TensorFlow
  ☆240Updated 2 weeks ago
• patrick-kidger / torchcde
  Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
  ☆453Updated last month
• probabilistic-numerics / probnum
  Probabilistic Numerics in Python.
  ☆458Updated 3 months ago
• msurtsukov / neural-ode
  Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
  ☆784Updated last year
• martius-lab / EQL
  Equation Learner, a neural network approach to symbolic regression
  ☆83Updated last year
• google-deepmind / mathematics_conjectures
  ☆375Updated 3 years ago
• GilpinLab / dysts
  Hundreds of strange attractors
  ☆496Updated last month
• Rachnog / Neural-ODE-Experiments
  This repository contains experiments with Neural Ordinary Differential Equations with simulated and real empirical data
  ☆199Updated 6 years ago