Alternatives and similar repositories for GIN

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

• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆38Updated 5 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆48Updated 6 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆61Updated 2 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆35Updated 4 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• ermongroup / smile-mi-estimator
  PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"
  ☆75Updated 5 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆36Updated 3 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 3 years ago
• akekic / causal-component-analysis
  ☆25Updated last year
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆50Updated 4 years ago
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago
• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆78Updated 3 years ago
• nickruggeri / CLAP-interpretable-predictions
  Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".
  ☆14Updated 3 years ago
• yixinwang / representation-causal-public
  ☆44Updated 3 years ago
• slachapelle / disentanglement_via_mechanism_sparsity
  ☆18Updated last year
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆86Updated last year
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆74Updated 3 years ago
• namratadeka / circe
  Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)
  ☆21Updated 2 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆76Updated 3 years ago
• ysharma1126 / ssl_identifiability
  Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
  ☆53Updated 3 years ago
• biomedia-mira / deepscm
  Repository for Deep Structural Causal Models for Tractable Counterfactual Inference
  ☆287Updated 2 years ago
• tristandeleu / jax-dag-gflownet
  Code for "Bayesian Structure Learning with Generative Flow Networks"
  ☆89Updated 3 years ago
• cyz-ai / neural-approx-ss-lfi
  Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models
  ☆20Updated 3 years ago
• kurowasan / GraN-DAG
  ☆96Updated 2 years ago
• capybaralet / REx_code_release
  ☆63Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago