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.
R interface to fast.ai
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.
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.
OLAP PivotTable Extensions is an Excel add-in which extends the functionality of PivotTables on Analysis Services cubes and of the Excel Data Model (Power Pivot)
Official PyTorch implementation of STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables (ICLR 2023 Spotlight).
Easily get custom go template based outputs to your command-line tool. Like in docker/kubernetes
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.
A tool for customizing and dynamically generating a tabular model from an existing tabular model.
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