Alternatives and similar repositories for SCM-VAE

Users that are interested in SCM-VAE are comparing it to the libraries listed below

• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆49Updated 6 years ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆63Updated 3 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆39Updated 5 years ago
• ErdunGAO / FedDAG
  [TMLR23] FedDAG: Federated DAG Structure Learning
  ☆18Updated 2 years ago
• vanderschaarlab / DECAF
  DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
  ☆21Updated 5 months ago
• weitianxin / awesome-distribution-shift
  A curated list of papers and resources about the distribution shift in machine learning.
  ☆123Updated 2 years ago
• kohpangwei / group_DRO
  Distributionally robust neural networks for group shifts
  ☆286Updated 2 years ago
• MaheepChaudhary / Causality-in-Trustworthy-Machine-Learning
  The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era comp…
  ☆98Updated 2 years ago
• facebookresearch / InvariantRiskMinimization
  PyTorch code to run synthetic experiments.
  ☆430Updated 4 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆34Updated 4 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆57Updated last year
• charan223 / FairDeepLearning
  ☆37Updated 2 years ago
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago
• linyongver / Bayesian-Invariant-Risk-Minmization
  This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.
  ☆46Updated 2 years ago
• namratadeka / circe
  Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)
  ☆21Updated 3 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• oscarkey / explanations-by-minimizing-uncertainty
  Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"
  ☆19Updated 4 years ago
• Valentyn1997 / CausalTransformer
  Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"
  ☆169Updated last year
• XTxiatong / PaperArxiv
  This is an Uncertainty Study Arxiv
  ☆11Updated 9 months ago
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆33Updated 4 years ago
• steven7woo / fair_regression_reduction
  General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.
  ☆16Updated 5 years ago
• Biwei-Huang / Causal-Discovery-from-Nonstationary-Heterogeneous-Data
  Causal Discovery from Nonstationary/Heterogeneous Data.
  ☆55Updated 5 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆39Updated 3 years ago
• paulrolland1307 / SCORE
  Code used in the paper "Score matching enables causal discovery of nonlinear additive noise models", Rolland et al., ICML 2022
  ☆21Updated 2 months ago
• kurowasan / GraN-DAG
  ☆97Updated 2 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• vanderschaarlab / Datagnosis
  A Data-Centric library providing a unified interface for state-of-the-art methods for hardness characterisation of data points.
  ☆25Updated 9 months ago
• divyat09 / cate-estimator-selection
  Code accompanying the paper "Empirical analysis of model selection for heterogeneous causal effect estimation"
  ☆14Updated 10 months ago
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆103Updated 3 years ago
• JakobCode / UncertaintyInNeuralNetworks_Resources
  ☆109Updated 4 years ago