Alternatives and similar repositories for cINN

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

• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆25Updated 5 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆121Updated 2 years ago
• thegialeo / Training-Invertible-Neural-Networks-as-Autoencoders
  ☆20Updated 2 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 3 years ago
• tk-rusch / coRNN
  Official code for Coupled Oscillatory RNN (ICLR 2021, Oral)
  ☆50Updated 4 years ago
• abdulfatir / planar-flow-pytorch
  Pytorch implementation of Planar Flow
  ☆17Updated 5 years ago
• e-hulten / maf
  PyTorch implementation of the Masked Autoregressive Flow
  ☆30Updated 4 years ago
• siplab-gt / VAELLS
  Code for "Variational Autoencoder with Learned Latent Structure"
  ☆34Updated 4 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆78Updated 2 years ago
• dimkal89 / rvae
  ☆37Updated 5 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 4 years ago
• spbu-math-cs / Riemannian-Gaussian-Processes
  Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".
  ☆29Updated 9 months ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• hanyas / mimo
  A toolbox for inference of mixture models
  ☆16Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆75Updated 3 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆42Updated 3 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆57Updated last year
• gpapamak / snl
  Sequential Neural Likelihood
  ☆42Updated 6 years ago
• ebonilla / gaussianprocesses
  Modern Gaussian Processes: Scalable Inference and Novel Applications
  ☆20Updated 6 years ago
• VMBoehm / PAE
  Probabilistic Auto-Encoder
  ☆43Updated 2 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• jungtaekkim / bayeso-benchmarks
  Benchmark functions for Bayesian optimization
  ☆37Updated last year
• weixsong / NormalizingFlow
  Implementation of different Normalizing Flows, NF, Planar Flows, IAF, etc.
  ☆30Updated 7 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• changliu00 / AWGF
  Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)
  ☆22Updated 5 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆43Updated 3 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago