Alternatives and similar repositories for SDCIT

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

• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• kurowasan / GraN-DAG
  ☆92Updated 2 years ago
• eberharf / fges-py
  ☆18Updated 5 years ago
• WY-Chen / EqVarDAG
  Causal Discovery with Equal Variance Assumption
  ☆9Updated 3 years ago
• sweichwald / tidybench
  TIme series DiscoverY BENCHmark (tidybench)
  ☆37Updated last year
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• slachapelle / dcdi
  Repository for "Differentiable Causal Discovery from Interventional Data"
  ☆74Updated 3 years ago
• WeijiaZhang24 / TEDVAE
  Code for TEDVAE, a VAE-based treatment effect estimation algorithm.
  ☆25Updated 2 years ago
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆32Updated 3 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 3 years ago
• ignavierng / notears-tensorflow
  Reimplementation of NOTEARS in Tensorflow
  ☆35Updated 2 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆35Updated 2 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆82Updated last year
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆35Updated 4 years ago
• ElementAI / causal_discovery_toolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆30Updated 5 years ago
• ermongroup / BCD-Nets
  Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
  ☆26Updated 3 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 2 years ago
• christinaheinze / core
  TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".
  ☆10Updated 6 years ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆60Updated 2 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• amber0309 / ANM-MM
  Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"
  ☆22Updated 5 years ago
• zhushy / causal-datasets
  Datasets for Causal-Structure-Learning Repo
  ☆15Updated 5 years ago
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆50Updated 6 years ago
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆47Updated 5 years ago
• sudiptodip15 / CCMI
  Classifier based mutual information, conditional mutual information estimation; conditional independence testing
  ☆34Updated 5 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 3 years ago
• oxcsml / kerpy
  python code for kernel methods
  ☆38Updated 6 years ago
• christinaheinze / nonlinearICP-and-CondIndTests
  Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents…
  ☆17Updated 5 years ago
• ioanabica / Counterfactual-Recurrent-Network
  Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…
  ☆59Updated last year
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 8 years ago