Alternatives and similar repositories for ACE

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

• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆104Updated 5 years ago
• charmlab / recourse
  Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
  ☆36Updated 2 years ago
• iancovert / removal-explanations
  A lightweight implementation of removal-based explanations for ML models.
  ☆58Updated 4 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆131Updated 5 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆53Updated 4 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆35Updated 4 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆50Updated 4 years ago
• lightlightdyy / Deep-Learning-and-Causal-Inference
  ☆29Updated 6 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 3 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• OscarcarLi / PrototypeDL
  Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…
  ☆75Updated 7 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 5 years ago
• AmanDaVinci / SENN
  Self-Explaining Neural Networks
  ☆42Updated 5 years ago
• ec6dde01667145e58de60f864e05a4 / CausalOptimizationAnon
  ☆65Updated last year
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆42Updated 5 years ago
• suinleelab / attributionpriors
  Tools for training explainable models using attribution priors.
  ☆124Updated 4 years ago
• laura-rieger / deep-explanation-penalization
  Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…
  ☆128Updated 4 years ago
• dmelis / SENN
  Self-Explaining Neural Networks
  ☆13Updated 2 years ago
• SeojinBang / VIBI
  Explaining a black-box using Deep Variational Information Bottleneck Approach
  ☆46Updated 2 years ago
• sfme / RVAE_MixedTypes
  Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)
  ☆50Updated 5 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆129Updated 4 years ago
• sjblim / rmsn_nips_2018
  ☆40Updated 6 years ago
• VirgiAgl / CausalBayesianOptimization
  Code for the Causal Bayesian Optimization algorithm (http://proceedings.mlr.press/v108/aglietti20a/aglietti20a.pdf)
  ☆30Updated 4 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆62Updated 5 years ago
• capybaralet / REx_code_release
  ☆63Updated 4 years ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 3 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago