Alternatives and similar repositories for Composite-Feature-Selection

Users that are interested in Composite-Feature-Selection are comparing it to the libraries listed below

• chl8856 / SEFS
  Codebase for SEFS: Self-Supervision Enhanced Feature Selection with Correlated Gates
  ☆23Updated last year
• huaxiuyao / C-Mixup
  C-Mixup for NeurIPS 2022
  ☆71Updated last year
• andreimargeloiu / WPFS
  Weight Predictor Networks with Sparse Feature Selection for Small Size Tabular Biomedical Data. Published at AAAI 2023
  ☆17Updated 2 years ago
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆102Updated 4 years ago
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated last year
• LARS-research / TabGNN
  ☆51Updated 3 years ago
• lauramanduchi / DC-GMM
  This repository holds the code for the paper "Deep Conditional Gaussian Mixture Model forConstrained Clustering".
  ☆34Updated 3 years ago
• layer6ai-labs / WinIT
  Code for the ICLR'23 paper "Temporal Dependencies in Feature Importance for Time Series Prediction"
  ☆26Updated 2 years ago
• IsolationKernel / Codes
  ☆51Updated 7 months ago
• wanyu-lin / ICML2021-Gem
  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."
  ☆67Updated 3 years ago
• vios-s / DiffAN
  Diffusion Models for Causal Discovery
  ☆85Updated 2 years ago
• facebookresearch / infoshap
  Codebase for information theoretic shapley values to explain predictive uncertainty.This repo contains the code related to the paperWatso…
  ☆21Updated last year
• snap-stanford / conformalized-gnn
  Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)
  ☆82Updated last year
• pfnet-research / TabCSDI
  A code for the NeurIPS 2022 Table Representation Learning Workshop paper: "Diffusion models for missing value imputation in tabular data"
  ☆51Updated last year
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• BaiTheBest / DRAIN
  GitHub Repo for ICLR 2023 Paper "Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks"
  ☆58Updated 2 years ago
• JunwenBai / C-GMVAE
  C-GMVAE: Gaussian Mixture VAE with Contrastive Learning for Multi-Label Classification
  ☆55Updated 2 years ago
• JointEntropy / awesome-ml-pu-learning
  A curated list of resources dedicated to Positive Unlabeled(PU) learning ML methods.
  ☆37Updated 2 years ago
• ahmedmalaa / evaluating-generative-models
  ☆21Updated 2 years ago
• lazaratan / dyn-gfn
  DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
  ☆55Updated last year
• willyfh / graph-transformer
  An unofficial implementation of Graph Transformer (Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classificat…
  ☆33Updated last year
• sanatonek / time_series_explainability
  ☆61Updated 4 years ago
• KevinMoonLab / GRAE
  Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning
  ☆24Updated last year
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆24Updated 2 years ago
• wangyongjie-ntu / CFAI
  A collection of algorithms of counterfactual explanations.
  ☆50Updated 4 years ago
• LFhase / PAIR
  [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
  ☆52Updated last year
• ganmodokix / gwae
  PyTorch Implementation for Gromov-Wasserstein Autoencoders (GWAE)
  ☆43Updated 2 years ago
• ngoc-nguyen-0 / DGG
  Linxiao Yang, Ngai-Man Cheung, Jiaying Li, and Jun Fang, "Deep Clustering by Gaussian Mixture Variational Autoencoders with Graph Embeddi…
  ☆52Updated 5 years ago
• diningphil / graph-mixture-density-networks
  Official Repository of "Graph Mixture Density Networks" (ICML 2021)
  ☆26Updated 3 years ago
• lemeln / nam
  Neural Additive Models (Google Research)
  ☆28Updated last year