Alternatives and similar repositories for fsic-test

Users that are interested in fsic-test are comparing it to the libraries listed below

• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated 10 months ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated last year
• oxcsml / kerpy
  python code for kernel methods
  ☆38Updated 6 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• rajatsen91 / CCIT
  Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing
  ☆45Updated last year
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆84Updated 4 years ago
• wittawatj / kernel-cgof
  UAI 2020. Kernel goodness-of-fit tests for conditional density models.
  ☆10Updated 4 years ago
• sudiptodip15 / CCMI
  Classifier based mutual information, conditional mutual information estimation; conditional independence testing
  ☆34Updated 5 years ago
• iffsid / DReG-PyTorch
  A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"
  ☆18Updated 5 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆35Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆32Updated 3 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆66Updated 3 months ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆40Updated 5 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 6 years ago
• ialong / GPt
  Gaussian Processes for Sequential Data
  ☆18Updated 4 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 9 months ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 8 years ago
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆39Updated 3 years ago
• kasparmartens / c-GPLVM
  PyTorch implementation of the Covariate-GPLVM
  ☆26Updated 5 years ago