Alternatives and similar repositories for neural-interaction-detection

Users that are interested in neural-interaction-detection are comparing it to the libraries listed below

• probabilistic-learning / HI-VAE
  ☆91Updated 2 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆62Updated 5 years ago
• mfbalin / Concrete-Autoencoders
  ☆118Updated 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
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆131Updated 4 years ago
• ioanabica / Counterfactual-Recurrent-Network
  Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…
  ☆59Updated last year
• steveli / misgan
  MisGAN: Learning from Incomplete Data with GANs
  ☆82Updated last year
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆101Updated 4 years ago
• gemoran / sparse-vae-code
  ☆32Updated 2 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…
  ☆75Updated 7 years ago
• sjblim / rmsn_nips_2018
  ☆40Updated 6 years ago
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated last year
• unnir / CancelOut
  CancelOut is a special layer for deep neural networks that can help identify a subset of relevant input features for streaming or static …
  ☆26Updated 4 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• OctoberChang / klcpd_code
  Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)
  ☆59Updated 2 years ago
• runopti / stg
  Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)
  ☆108Updated 3 years ago
• Piyushi-0 / ACE
  Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.
  ☆51Updated 3 years ago
• suinleelab / attributionpriors
  Tools for training explainable models using attribution priors.
  ☆124Updated 4 years ago
• ratschlab / SOM-VAE
  TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199
  ☆197Updated 2 years ago
• Jianbo-Lab / L2X
  ☆124Updated 4 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
• sudiptodip15 / CCMI
  Classifier based mutual information, conditional mutual information estimation; conditional independence testing
  ☆34Updated 5 years ago
• GoudetOlivier / CGNN
  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
  ☆100Updated 6 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
• ayaabdelsalam91 / TS-Interpretability-Benchmark
  ☆91Updated 3 years ago
• weirayao / leap
  LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.
  ☆35Updated 2 years ago
• kurowasan / GraN-DAG
  ☆93Updated 2 years ago
• inouye-lab / ShapleyExplanationNetworks
  Implementation of the paper "Shapley Explanation Networks"
  ☆88Updated 4 years ago
• maxwshen / iap-cidl
  Causal Inference & Deep Learning, MIT IAP 2018
  ☆89Updated 7 years ago