Alternatives and similar repositories for cfqp

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

• JeanKaddour / SIN
  Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
  ☆43Updated 3 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆27Updated 6 months ago
• ahujak / IB-IRM
  ☆31Updated 4 years ago
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆26Updated 2 years ago
• caus-am / dom_adapt
  Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"
  ☆18Updated 4 years ago
• mertyg / beyond-confidence-atypicality
  Repository for the NeurIPS 2023 paper "Beyond Confidence: Reliable Models Should Also Consider Atypicality"
  ☆13Updated last year
• zhougroup / BAM
  Bayesian Attention Modules
  ☆35Updated 4 years ago
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆87Updated 2 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆26Updated 3 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 5 years ago
• BaeHeeSun / NPC
  ☆25Updated last year
• belaalb / CEVAE-VampPrior
  CEVAE with VampPrior
  ☆11Updated 7 years ago
• acmi-lab / PU_learning
  Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotligh…
  ☆44Updated last year
• mymakar / causally_motivated_shortcut_removal
  ☆14Updated 2 years ago
• changliu00 / causal-semantic-generative-model
  Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …
  ☆76Updated 3 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆62Updated 3 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆51Updated 4 years ago
• yixinwang / representation-causal-public
  ☆44Updated 3 years ago
• karenyang / GCN-VAE
  project GCN-VAE for knowledge graphs
  ☆16Updated 5 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆35Updated 4 years ago
• phlippe / ENCO
  Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"
  ☆86Updated last year
• autumn9999 / MTC-with-Category-Shifts
  ☆12Updated 3 years ago
• linyongver / ZIN_official
  This is the implementation for the NeurIPS 2022 paper: ZIN: When and How to Learn Invariance Without Environment Partition?
  ☆22Updated 2 years ago
• AMLab-Amsterdam / DataAugmentationInterventions
  ☆26Updated 5 years ago
• wanyu-lin / ICML2021-Gem
  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."
  ☆68Updated 3 years ago
• huaxiuyao / Wild-Time
  Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)
  ☆67Updated 2 years ago
• ermongroup / BCD-Nets
  Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
  ☆26Updated 4 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆38Updated 3 years ago
• Daftstone / CIMI
  ☆28Updated 2 years ago