Alternatives and similar repositories for neural-interaction-detection:

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

• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago
• probabilistic-learning / HI-VAE
  ☆90Updated 2 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆60Updated 4 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆130Updated 4 years ago
• gemoran / sparse-vae-code
  ☆32Updated 2 years ago
• Jianbo-Lab / L2X
  ☆125Updated 3 years ago
• steveli / misgan
  MisGAN: Learning from Incomplete Data with GANs
  ☆81Updated last year
• sudiptodip15 / CCMI
  Classifier based mutual information, conditional mutual information estimation; conditional independence testing
  ☆34Updated 5 years ago
• oxcsml / kerpy
  python code for kernel methods
  ☆38Updated 6 years ago
• younglululu / DeepPINK
  DeepPINK: reproducible feature selection in deep neural networks
  ☆21Updated last year
• mtsang / interaction_interpretability
  Feature Interaction Interpretability via Interaction Detection
  ☆34Updated last year
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆83Updated 6 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆49Updated 3 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• OctoberChang / klcpd_code
  Kernel Change-point Detection with Auxiliary Deep Generative Models (ICLR 2019 paper)
  ☆58Updated last year
• suinleelab / attributionpriors
  Tools for training explainable models using attribution priors.
  ☆124Updated 4 years ago
• GoudetOlivier / CGNN
  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
  ☆99Updated 5 years ago
• Harry24k / MIDA-pytorch
  PyTorch implementation of "MIDA: Multiple Imputation using Denoising Autoencoders"
  ☆28Updated 6 years ago
• muhanzhang / D-VAE
  D-VAE: A Variational Autoencoder for Directed Acyclic Graphs, NeurIPS 2019
  ☆138Updated 4 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.
  ☆30Updated 5 years ago
• dtak / hs-bnn-public
  ☆12Updated 7 years ago
• msesia / deepknockoffs
  Approximate knockoffs and model-free variable selection.
  ☆54Updated 3 years ago
• alexlyzhov / latent-subspaces
  Implementation of "Learning latent subspaces in variational autoencoders"
  ☆20Updated 5 years ago
• ratschlab / SOM-VAE
  TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199
  ☆196Updated 2 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
• 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
• inouye-lab / ShapleyExplanationNetworks
  Implementation of the paper "Shapley Explanation Networks"
  ☆88Updated 4 years ago
• amber0309 / HSIC
  Python code of Hilbert-Schmidt Independence Criterion
  ☆87Updated 2 years ago
• eelxpeng / ltvae-release
  ☆22Updated 5 years ago
• sjblim / rmsn_nips_2018
  ☆38Updated 6 years ago