Alternatives and similar repositories for DEAR

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

• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆47Updated 6 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆36Updated 2 years ago
• patrickrchao / DiffusionBasedCausalModels
  ☆26Updated 3 months 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 …
  ☆74Updated 3 years ago
• ysharma1126 / ssl_identifiability
  Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
  ☆53Updated 3 years ago
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆32Updated 3 years ago
• kurowasan / GraN-DAG
  ☆93Updated 2 years ago
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆24Updated 2 years ago
• namratadeka / circe
  Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)
  ☆21Updated 2 years ago
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆85Updated 2 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆37Updated 5 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆102Updated 4 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 4 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 3 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.
  ☆31Updated 5 years ago
• ermongroup / BCD-Nets
  Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021
  ☆26Updated 3 years ago
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆46Updated 4 years ago
• yixinwang / representation-causal-public
  ☆44Updated 3 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆34Updated 4 years ago
• GuHY777 / VaDE-pytorch
  the reproduce of Variational Deep Embedding : A Generative Approach to Clustering Requirements by pytorch
  ☆136Updated 2 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 4 years ago
• octeufer / Adversarial-Balancing-based-representation-learning-for-Causal-Effect-Inference
  Causal Inference
  ☆10Updated 5 years ago
• oscarkey / explanations-by-minimizing-uncertainty
  Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"
  ☆18Updated 4 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 3 years ago
• capybaralet / REx_code_release
  ☆63Updated 4 years ago
• danielgreenfeld3 / XIC
  Robust Learning with the Hilbert-Schmidt Independence Criterion
  ☆47Updated 5 years ago
• ermongroup / smile-mi-estimator
  PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"
  ☆74Updated 5 years ago
• vanderschaarlab / DECAF
  DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
  ☆21Updated last month