Alternatives and similar repositories for deep_tabular_augmentation

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

• ryancheunggit / tabular_dae
  ☆53Updated 2 years ago
• NextBrain-ai / nbsynthetic
  nbsynthetic is simple and robust tabular synthetic data generation library for small and medium size datasets
  ☆69Updated 2 years ago
• AstraZeneca / SubTab
  The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
  ☆150Updated 3 years ago
• tusharsarkar3 / XBNet
  Boosted neural network for tabular data
  ☆217Updated last year
• LevinRoman / tabular-transfer-learning
  A repo for transfer learning with deep tabular models
  ☆105Updated 2 years ago
• radi-cho / GatedTabTransformer
  A deep learning tabular classification architecture inspired by TabTransformer with integrated gated multilayer perceptron.
  ☆101Updated 2 years ago
• aruberts / TabTransformerTF
  TensorFlow implementation of TabTransformer
  ☆84Updated 2 years ago
• bits-bytes-nn / mofc-demand-forecast
  Time Series Forecasting for the M5 Competition
  ☆41Updated 4 years ago
• ykwon0407 / WeightedSHAP
  WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)
  ☆159Updated 3 years ago
• h3ik0th / ES_energy_Transformer
  Python Darts deep forecasting models
  ☆34Updated 3 years ago
• lmassaron / deep-learning-for-tabular-data
  An updated (2025) guide to Deep Learning for tabular data, comparing a fine-tuned Keras 3 (PyTorch backend) DNN and an Optuna-optimized…
  ☆47Updated 4 months ago
• callmeBalloch / google-brain-ventilator-pressure-prediction
  ☆27Updated 4 years ago
• CoteDave / blog
  ☆63Updated 2 years ago
• philipdarke / torchtime
  Benchmark time series data sets for PyTorch
  ☆36Updated last year
• puhsu / tabular-dl-pretrain-objectives
  Revisiting Pretrarining Objectives for Tabular Deep Learning
  ☆65Updated 3 years ago
• atif-hassan / FRUFS
  An unsupervised feature selection technique using supervised algorithms such as XGBoost
  ☆90Updated last year
• kathrinse / TabSurvey
  Experiments on Tabular Data Models
  ☆281Updated 2 years ago
• YousefGh / kmeans-feature-importance
  Adding feature_importances_ property to sklearn.cluster.KMeans class
  ☆64Updated 2 years ago
• feedzai / timeshap
  TimeSHAP explains Recurrent Neural Network predictions.
  ☆193Updated 2 years ago
• TannerGilbert / Model-Interpretation
  Overview of different model interpretability libraries.
  ☆51Updated 3 years ago
• guitarmind / kaggle_moa_winner_hungry_for_gold
  Winning Solution of Kaggle Mechanisms of Action (MoA) Prediction.
  ☆122Updated 3 years ago
• jrzaurin / tabulardl-benchmark
  Benchmark tabular Deep Learning models against each other and other non-DL techniques
  ☆57Updated 4 years ago
• atif-hassan / PyImpetus
  PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in…
  ☆140Updated 10 months ago
• zhuyitan / IGTD
  Image Generator for Tabular Data (IGTD): Converting Tabular Data to Images for Deep Learning Using Convolutional Neural Networks
  ☆170Updated last year
• machinelearningnuremberg / WellTunedSimpleNets
  [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets
  ☆88Updated 2 years ago
• gkunapuli / ensemble-methods-notebooks
  A collection of companion Jupyter notebooks for Ensemble Methods for Machine Learning (Manning, 2023)
  ☆91Updated 2 years ago
• MathiasKraus / igann
  ☆45Updated 3 months ago
• interpretml / TalkToEBM
  A Natural Language Interface to Explainable Boosting Machines
  ☆69Updated last year
• fzi-forschungszentrum-informatik / TSInterpret
  An Open-Source Library for the interpretability of time series classifiers
  ☆144Updated last month
• LocalCascadeEnsemble / LCE
  Random Forest or XGBoost? It is Time to Explore LCE
  ☆70Updated 2 years ago