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
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 3 years ago
• lindonroberts / trust-region
  Python trust-region subproblem solvers for nonlinear optimization
  ☆28Updated last year
• cselab / LED
  ☆21Updated 2 years ago
• dynamicslab / langevin-regression
  Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton
  ☆26Updated 3 years ago
• samuelkim314 / DeepSymRegTorch
  PyTorch implementation of the EQL network, a neural network for symbolic regression
  ☆41Updated 4 years ago
• josephbakarji / bucki-data
  Machine learning algorithms for discovering dimensionless groups from simulation and experimental data
  ☆13Updated 2 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 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
• lorenzrichter / PDE-backward-solver
  ☆22Updated 10 months ago
• IdahoLabResearch / BIhNNs
  The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …
  ☆15Updated 2 years ago
• AdrienCorenflos / particle_mala
  Gradient-informed particle MCMC methods
  ☆12Updated last year
• Rose-STL-Lab / Equivariant-Net
  ☆35Updated 2 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 3 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
• li012589 / HMC_pytorch
  A pytorch version of hamiltonian monte carlo
  ☆14Updated 6 years ago
• luckystarufo / multiscale_HiTS
  ☆73Updated 5 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• aidanscannell / GPJax
  Minimal Gaussian process library in JAX with a simple (custom) approach to state management.
  ☆12Updated last year
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• AlexTMallen / koopman-forecasting
  Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory
  ☆35Updated 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
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• ZichaoLong / aTEAM
  A pyTorch Extension for Applied Mathematics
  ☆40Updated 5 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆110Updated 4 years ago
• LRydin / KramersMoyal
  kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order
  ☆74Updated 8 months ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• fidero / gp-derivative
  Example code to speed up GP inference with gradients for high-dimensional inputs.
  ☆14Updated 4 years ago
• DurstewitzLab / ChaosRNN
  ☆19Updated 2 years ago