kathrinse / be_great
A novel approach for synthesizing tabular data using pretrained large language models
☆296Updated 3 months ago
Alternatives and similar repositories for be_great:
Users that are interested in be_great are comparing it to the libraries listed below
- A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.☆220Updated 2 months ago
- Experiments on Tabular Data Models☆272Updated last year
- [ICML 2023] The official implementation of the paper "TabDDPM: Modelling Tabular Data with Diffusion Models"☆420Updated 7 months ago
- The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"☆281Updated 3 months ago
- ☆469Updated 5 months ago
- A framework for prototyping and benchmarking imputation methods☆174Updated last year
- Benchmarking synthetic data generation methods.☆267Updated this week
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆160Updated 2 years ago
- Official git for "CTAB-GAN: Effective Table Data Synthesizing"☆82Updated last year
- ☆141Updated 10 months ago
- A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.☆515Updated last month
- Metrics to evaluate quality and efficacy of synthetic datasets.☆222Updated this week
- ☆67Updated 2 months ago
- Official git for "TabuLa: Harnessing Language Models for Tabular Data Synthesis"☆37Updated 3 months ago
- A collection of research materials on SSL for non-sequential tabular data (SSL4NSTD)☆175Updated this week
- Official Implementations of "Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space""☆119Updated 7 months ago
- A Natural Language Interface to Explainable Boosting Machines☆64Updated 7 months ago
- Official GitHub for CTAB-GAN+☆73Updated 9 months ago
- A repo for transfer learning with deep tabular models☆102Updated 2 years ago
- nbsynthetic is simple and robust tabular synthetic data generation library for small and medium size datasets☆64Updated last year
- The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive …☆413Updated 3 years ago
- For calculating global feature importance using Shapley values.☆264Updated this week
- ☆64Updated last year
- Compare and ensemble models without retraining☆45Updated this week
- ☆289Updated last year
- Semi-automatic feature engineering process using Language Models and your dataset descriptions. Based on the paper "LLMs for Semi-Automat…☆146Updated last month
- Revisiting Pretrarining Objectives for Tabular Deep Learning☆63Updated 2 years ago
- Tabular Deep Learning Library for PyTorch☆611Updated this week
- ☆26Updated last year
- Generating and Imputing Tabular Data via Diffusion and Flow XGBoost Models☆148Updated 6 months ago