Alternatives and similar repositories for INVASE

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

• sfme / RVAE_MixedTypes
  Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)
  ☆48Updated 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…
  ☆67Updated last year
• iancovert / removal-explanations
  A lightweight implementation of removal-based explanations for ML models.
  ☆59Updated 4 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆132Updated 5 years ago
• OATML / ucate
  Uncertainty in Conditional Average Treatment Effect Estimation
  ☆33Updated 4 years ago
• mtsang / neural-interaction-detection
  Detecting Statistical Interactions from Neural Network Weights
  ☆49Updated 5 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆35Updated 5 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆54Updated 5 years ago
• Piyushi-0 / ACE
  Code for our ICML '19 oral paper: Neural Network Attributions: A Causal Perspective.
  ☆51Updated 4 years ago
• sjblim / rmsn_nips_2018
  ☆40Updated 7 years ago
• Jianbo-Lab / L2X
  ☆125Updated 4 years ago
• probabilistic-learning / HI-VAE
  ☆93Updated 2 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆129Updated 4 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆104Updated 5 years ago
• JonathanCrabbe / Simplex
  This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help …
  ☆24Updated 3 years ago
• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆43Updated 3 years ago
• mrojascarulla / causal_transfer_learning
  ☆33Updated 7 years ago
• mtsang / interaction_interpretability
  Feature Interaction Interpretability via Interaction Detection
  ☆35Updated 2 years ago
• suinleelab / attributionpriors
  Tools for training explainable models using attribution priors.
  ☆125Updated 4 years ago
• microsoft / EDDI
  Code for paper EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
  ☆43Updated 2 years ago
• AmrMKayid / nam
  Neural Additive Models (Google Research)
  ☆74Updated 4 years ago
• rsheth80 / pmf-automl
  Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.
  ☆40Updated 4 years ago
• OscarcarLi / PrototypeDL
  Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…
  ☆77Updated 8 years ago
• GoudetOlivier / CGNN
  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
  ☆100Updated 6 years ago
• AmanDaVinci / SENN
  Self-Explaining Neural Networks
  ☆44Updated 6 years ago
• maxwshen / iap-cidl
  Causal Inference & Deep Learning, MIT IAP 2018
  ☆89Updated 8 years ago
• belaalb / CEVAE-VampPrior
  CEVAE with VampPrior
  ☆11Updated 7 years ago
• amiratag / DistributionalShapley
  Distributional Shapley: A Distributional Framework for Data Valuation
  ☆30Updated last year
• lightlightdyy / Deep-Learning-and-Causal-Inference
  ☆30Updated 7 years ago
• runopti / stg
  Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)
  ☆110Updated 3 years ago