Alternatives and similar repositories for GCIT

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

• kjchalup / independence_test
  A deep-learning-based conditional independence test that works for big, high-dimensional data.
  ☆14Updated 7 years ago
• rajatsen91 / CCIT
  Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing
  ☆45Updated 2 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆37Updated 5 years ago
• msesia / deepknockoffs
  Approximate knockoffs and model-free variable selection.
  ☆55Updated 3 years ago
• christinaheinze / core
  TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".
  ☆10Updated 6 years ago
• wittawatj / fsic-test
  ICML 2017. Kernel-based adaptive linear-time independence test.
  ☆17Updated 3 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 3 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆76Updated 3 years ago
• alexisthual / fugw
  Scalable python GPU solvers for fused unbalanced gromov-wasserstein optimal transport problems, with routines and examples to align brain…
  ☆41Updated last month
• 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
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆32Updated 3 years ago
• gemoran / sparse-vae-code
  ☆32Updated 2 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated 2 years ago
• rachtsingh / ibp_vae
  mean-field and structured VAEs for the IBP
  ☆23Updated 7 years ago
• uhlerlab / actlearn_optint
  Active learning for optimal intervention design in causal models
  ☆16Updated last year
• victorkristof / linear-regressions-mixture
  Python implementation of mixtures of linear regressions.
  ☆14Updated 5 years ago
• amber0309 / HSIC
  Python code of Hilbert-Schmidt Independence Criterion
  ☆87Updated 3 years ago
• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆50Updated last year
• mijungi / lllvm
  ☆16Updated 9 years ago
• fdtomasi / regain
  REGAIN (Regularised Graphical Inference)
  ☆29Updated 2 years ago
• nerdslab / PyHiWA
  Alignment between clustered datasets via hierarchical Wasserstein distance
  ☆38Updated last year
• willieneis / gp-martingales
  Uncertainty quantification using martingales for misspecified Gaussian processes
  ☆9Updated 4 years ago
• orilinial / GOKU
  Deep Generative ODE Modelling with Known Unknowns
  ☆18Updated 4 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆53Updated 4 years ago
• BiuBiuBiLL / NPEET_LNC
  local non-uniformity correction for mutual information estimation
  ☆70Updated 4 years ago
• uhlerlab / causaldag
  Python package for the creation, manipulation, and learning of Causal DAGs
  ☆152Updated 2 years ago
• wgao9 / knnie
  k-Nearest Neighbor Information Estimator
  ☆26Updated 6 years ago
• kasparmartens / c-GPLVM
  PyTorch implementation of the Covariate-GPLVM
  ☆25Updated 5 years ago
• PaulVanDev / HoeffdingD
  Efficient implementation of Hoeffding Distance in Python for large datasets
  ☆19Updated 5 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year