Research on Tabular Deep Learning: Papers & Packages
[ICML 2023] The official implementation of the paper "TabDDPM: Modelling Tabular Data with Diffusion Models"
Reactive datatables for large or small datasets
A comprehensive toolkit and benchmark for tabular data learning, featuring 30 deep methods, more than 10 classical methods, and 300 diverse tabular datasets.
Useful code for tabular modeling and automation.
Mambular is a Python package that brings the power of Mamba architectures to tabular data, offering a suite of deep learning models for regression, classification, and distributional regression tasks. This includes models like Mambular, FT-Transformer, TabTransformer and tabular ResNets.
R interface to fast.ai
TAT-QA (Tabular And Textual dataset for Question Answering) contains 16,552 questions associated with 2,757 hybrid contexts from real-world financial reports.
Data annotator for machine learning allows you to centrally create, manage and administer annotation projects for machine learning
A framework for dynamically creating a tabular model based on an Excel template.
Official PyTorch implementation of STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables (ICLR 2023 Spotlight).
OLAP PivotTable Extensions is an Excel add-in which extends the functionality of PivotTables on Analysis Services cubes, the Excel Data Model (Power Pivot), and Power BI
Easily get custom go template based outputs to your command-line tool. Like in docker/kubernetes
ML models + benchmark for tabular data classification and regression
Repository of web and code editor friendly Observable Data Toools 🛠️ and Notebooks 📚 in .js, .nb.json, .ojs, .omd, .html and .qmd document formats for Data Previews in a browser and in VSCode IDE with Observable JS extension, Quarto extension, and new Quarto publishing tools.
A tool for managing the processing of Analysis Services, Azure Analysis Services and Power BI Premium models.
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