Alternatives and similar repositories for Symbolic-Regression

Users that are interested in Symbolic-Regression are comparing it to the libraries listed below

• cfusting / fast-symbolic-regression
  Blazing fast symbolic regresison
  ☆76Updated 5 years ago
• martius-lab / EQL
  Equation Learner, a neural network approach to symbolic regression
  ☆82Updated 11 months ago
• Ambrosys / glyph
  a python 3 library based on deap providing abstraction layers for symbolic regression problems.
  ☆94Updated 3 years ago
• samuelkim314 / DeepSymReg
  Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"
  ☆76Updated 2 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 3 years ago
• marcovirgolin / SimpleGP
  Simple Genetic Programming for Symbolic Regression in Python3
  ☆25Updated 3 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆110Updated 4 years ago
• Rachnog / Neural-Networks-for-Differential-Equations
  UNIVR PDE course project and just for fun
  ☆117Updated 8 years ago
• eth-nn-physics / nn_physical_concepts
  ☆177Updated 2 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆246Updated 3 years ago
• martius-lab / EQL_Tensorflow
  Tensorflow implementation of equation learner
  ☆32Updated 4 years ago
• titu1994 / tfdiffeq
  Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
  ☆221Updated 5 years ago
• juliusberner / Deep-Multilevel-Kolmogorov-PDE-Solver
  Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation
  ☆12Updated 4 years ago
• numericalalgorithmsgroup / pybobyqa
  Python-based Derivative-Free Optimization with Bound Constraints
  ☆87Updated 11 months ago
• marcovirgolin / GP-GOMEA
  Genetic Programming version of GOMEA. Also includes standard tree-based GP, and Semantic Backpropagation-based GP
  ☆54Updated last year
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆119Updated 2 years ago
• luckystarufo / multiscale_HiTS
  ☆73Updated 4 years ago
• patrick-kidger / sympytorch
  Turning SymPy expressions into PyTorch modules.
  ☆149Updated 2 years ago
• abdulfatir / sampling-methods-numpy
  This repository contains implementations of some basic sampling methods in numpy.
  ☆67Updated 5 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• msmbuilder / vde
  Variational Autoencoder for Dimensionality Reduction of Time-Series
  ☆188Updated 3 years ago
• zi-w / Ensemble-Bayesian-Optimization
  Code repository for Ensemble Bayesian Optimization
  ☆54Updated 6 years ago
• pablormier / yabox
  Yet another black-box optimization library for Python
  ☆138Updated 2 years ago
• jmetzen / bayesian_optimization
  Bayesian optimization
  ☆38Updated 5 years ago
• samuelkim314 / DeepSymRegTorch
  PyTorch implementation of the EQL network, a neural network for symbolic regression
  ☆41Updated 4 years ago
• google-research / neural-structural-optimization
  Neural reparameterization improves structural optimization
  ☆123Updated 4 years ago
• amirgholami / anode
  [IJCAI'19, NeurIPS'19] Anode: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
  ☆107Updated 4 years ago
• li012589 / NeuralRG
  Pytorch source code for arXiv paper Neural Network Renormalization Group, a generative model using variational renormalization group and …
  ☆78Updated 5 years ago
• wujian16 / Cornell-MOE
  A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
  ☆268Updated 5 years ago
• timudk / SPDENN
  A Discussion on Solving Partial Differential Equations using Neural Networks
  ☆66Updated 6 years ago