Alternatives and similar repositories for FeatureImportanceDL

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

• inouye-lab / ShapleyExplanationNetworks
  Implementation of the paper "Shapley Explanation Networks"
  ☆88Updated 4 years ago
• ZhiningLiu1998 / mesa
  [NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题
  ☆110Updated last year
• BorisMuzellec / MissingDataOT
  A Pytorch implementation of missing data imputation using optimal transport.
  ☆103Updated 4 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆63Updated 5 years ago
• runopti / stg
  Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)
  ☆108Updated 3 years ago
• sungyubkim / MCDO
  A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
  ☆57Updated 6 years ago
• CompML / survey-distribution-shift
  Survey for Distribution Shift
  ☆19Updated 4 years ago
• VITA-Group / Self-PU
  [ICML2020] "Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training" by Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gon…
  ☆69Updated 3 years ago
• LARS-research / TabGNN
  ☆51Updated 4 years ago
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated 2 years ago
• v1xerunt / StageNet
  Source code for StageNet: Stage-Aware Neural Networks for Health Risk Prediction
  ☆31Updated 5 months ago
• AmrMKayid / nam
  Neural Additive Models (Google Research)
  ☆71Updated 4 years ago
• sheryl-ai / MetaPred
  MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records (KDD 2019)
  ☆48Updated 5 years ago
• iancovert / fastshap
  An amortized approach for calculating local Shapley value explanations
  ☆100Updated last year
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆30Updated 3 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆55Updated last year
• sanatonek / time_series_explainability
  ☆62Updated 4 years ago
• Lingkai-Kong / SDE-Net
  Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates
  ☆115Updated 4 years ago
• mfbalin / Concrete-Autoencoders
  ☆119Updated 3 years ago
• huyng / incertae
  Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments
  ☆70Updated 5 years ago
• TongtongFANG / DIW
  Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".
  ☆30Updated 4 years ago
• JunwenBai / MPVAE
  MPVAE: Multivariate Probit Variational AutoEncoder for Multi-Label Classification
  ☆32Updated last year
• takeshi-teshima / few-shot-domain-adaptation-by-causal-mechanism-transfer
  Implementation of Few-shot Domain Adaptation by Causal Mechanism Transfer (ICML 2020)
  ☆44Updated 2 years ago
• acmi-lab / PU_learning
  Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotligh…
  ☆44Updated last year
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆35Updated 4 years ago
• BorealisAI / ranksim-imbalanced-regression
  [ICML 2022] RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
  ☆52Updated 2 years ago
• weitianxin / awesome-distribution-shift
  A curated list of papers and resources about the distribution shift in machine learning.
  ☆123Updated 2 years ago
• ywatanabe1989 / custom_losses_pytorch
  Custom loss functions to use in (mainly) PyTorch.
  ☆39Updated 5 years ago
• chl8856 / AC_TPC
  AC_TPC: Temporal Phenotyping using Deep Predicting Clustering of Disease Progression
  ☆46Updated 4 years ago
• cimeister / pu-learning
  Pytorch implementation of risk estimators for unbiased and non-negative positive-unlabeled learning
  ☆91Updated last year