Abstract: Deep neural networks have been proved a success in multiple fields. However, researchers still favor traditional approaches to obtain more interpretable models, such as Bayesian methods and ...
Abstract: Synthetic tabular data generation becomes crucial when real data are limited, expensive to collect, or simply cannot be used due to privacy concerns. However, producing good quality ...
Awesome Tabular Deep Learning for "Representation Learning for Tabular Data: A Comprehensive Survey". If you use any content of this repo for your work, please cite the following bib entry: ...
This repository contains the code for our ICML 2023 paper: TabLeak: Tabular Data Leakage in Federated Learning. In case of any questions, feel free to contact us, either here, or per email to the ...
Herzig: SAP-RPT-1 is a foundation model built specifically for tabular business data – ledgers, invoices, inventories and other relational records. Importantly, it's not an LLM. LLMs are trained on ...
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