Alternatives and similar repositories for infoselect

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

• zzzace2000 / nodegam
  Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
  ☆47Updated 3 years ago
• LevinRoman / tabular-transfer-learning
  A repo for transfer learning with deep tabular models
  ☆104Updated 2 years ago
• a-norcliffe / Composite-Feature-Selection
  Official Code for the paper: "Composite Feature Selection using Deep Ensembles"
  ☆22Updated 2 years ago
• ahmedmalaa / evaluating-generative-models
  ☆21Updated 2 years ago
• udellgroup / controlburn
  ☆18Updated last year
• philipdarke / torchtime
  Benchmark time series data sets for PyTorch
  ☆36Updated last year
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year
• tfmortie / uaml
  Uncertainty-aware classification.
  ☆17Updated 3 years ago
• lpfgarcia / ECoL
  Extended Complexity Library in R
  ☆57Updated 4 years ago
• AmrMKayid / nam
  Neural Additive Models (Google Research)
  ☆71Updated 3 years ago
• riken-aip / pyHSICLasso
  Versatile Nonlinear Feature Selection Algorithm for High-dimensional Data
  ☆185Updated 3 years ago
• iancovert / removal-explanations
  A lightweight implementation of removal-based explanations for ML models.
  ☆58Updated 4 years ago
• msesia / arc
  Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems
  ☆31Updated 2 years ago
• team-daniel / MC-CP
  All the material needed to use MC-CP and the Adaptive MC Dropout method
  ☆24Updated 3 months ago
• machinelearningnuremberg / WellTunedSimpleNets
  [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets
  ☆86Updated 2 years ago
• paobranco / SMOGN-LIDTA17
  SMOGN: a Pre-processing Approach for Imbalanced Regression - LIDTA2017
  ☆25Updated 8 years ago
• kamilest / conformal-rnn
  Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.
  ☆75Updated 9 months ago
• nickfrosst / neural_additive_models
  stand alone Neural Additive Models, forked from google-reasearch for easy import to colab
  ☆28Updated 4 years ago
• sanatonek / time_series_explainability
  ☆61Updated 4 years ago
• runopti / stg
  Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)
  ☆108Updated 3 years ago
• singh-ml / fsnet
  ☆17Updated 4 years ago
• Pacmed / ehr_ood_detection
  Pacmed Labs experiments on uncertainty estimation, focusing on unbalanced tabular data and classification tasks.
  ☆21Updated 4 years ago
• mateoespinosa / remix
  Rule Extraction Methods for Interactive eXplainability
  ☆47Updated 3 years ago
• syanga / pycit
  (Conditional) Independence testing & Markov blanket feature selection using k-NN mutual information and conditional mutual information es…
  ☆30Updated 5 years ago
• aangelopoulos / conformal-risk
  Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…
  ☆67Updated 2 years ago
• AstraZeneca / SubTab
  The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
  ☆145Updated 3 years ago
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆74Updated last year
• tobias-freidling / hsic-lasso-psi
  Post-selection inference based on truncated Gaussians for the HSIC-Lasso feature selection procedure
  ☆10Updated 4 years ago
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated 2 years ago
• mfbalin / Concrete-Autoencoders
  ☆118Updated 3 years ago