Alternatives and similar repositories for cINNamon:

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

• PhIMaL / temporal_normalizing_flows
  ☆11Updated 4 years ago
• IdahoLabResearch / BIhNNs
  The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …
  ☆14Updated 2 years ago
• ZichaoLong / aTEAM
  A pyTorch Extension for Applied Mathematics
  ☆39Updated 5 years ago
• PredictiveScienceLab / inverse-bgo
  Use Bayesian Global Optimization to solve inverse problems
  ☆13Updated 9 years ago
• briandesilva / discovery-of-physics-from-data
  Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"
  ☆27Updated 4 years ago
• peterparity / PDE-VAE-pytorch
  PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning
  ☆35Updated 3 years ago
• li012589 / HMC_pytorch
  A pytorch version of hamiltonian monte carlo
  ☆14Updated 5 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• cselab / LED
  ☆19Updated 2 years ago
• lindonroberts / trust-region
  Python trust-region subproblem solvers for nonlinear optimization
  ☆29Updated 8 months ago
• snagcliffs / RKNN
  ☆20Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• dngfra / Restricted-Boltzmann-Machines
  Implementation of restricted Boltzmann machines in Tensorflow 2
  ☆28Updated last year
• stefanradev93 / cINN
  Contains legacy code and model examples for the paper "BayesFlow: Learning complex stochastic models with invertible neural networks"
  ☆22Updated 4 years ago
• twhughes / Symbolic-Regression
  predicting equations from raw data with deep learning
  ☆56Updated 6 years ago
• samuelkim314 / DeepSymRegTorch
  PyTorch implementation of the EQL network, a neural network for symbolic regression
  ☆39Updated 3 years ago
• josephbakarji / bucki-data
  Machine learning algorithms for discovering dimensionless groups from simulation and experimental data
  ☆12Updated 2 years ago
• samuelkim314 / DeepSymReg
  Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"
  ☆70Updated 2 years ago
• RehMoritz / vmc_pde
  Code for the paper "Variational Monte Carlo Approach to Partial Differential Equations with Neural Networks" (https://arxiv.org/abs/2206.…
  ☆10Updated 2 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆44Updated 5 years ago
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• Rose-STL-Lab / Equivariant-Net
  ☆35Updated last year
• SchatzLabGT / SymbolicRegression
  ☆11Updated 4 years ago
• sayin / Data_Driven_Symbolic_Regression
  Interpretable machine learning (symbolic regression) using Genetic programming/Gene expression programming and Sparse regression used …
  ☆34Updated 4 years ago
• jayroxis / qres
  Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)
  ☆15Updated 4 years ago
• Zymrael / PortHamiltonianNN
  Port-Hamiltonian Approach to Neural Network Training
  ☆22Updated 5 years ago
• PhIMaL / DeePyMoD_torch
  Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]
  ☆32Updated last year
• PredictiveIntelligenceLab / BayesianDifferentiableProgramming
  ☆21Updated 4 years ago
• lorenzrichter / path-space-PDE-solver
  ☆10Updated 3 years ago