Simple Modifications to Improve Tabular Neural Networks

6 August 2021

Papers citing "Simple Modifications to Improve Tabular Neural Networks"

8 / 8 papers shown

Title
Multi-annotator Deep Learning: A Probabilistic Framework for Classification M. Herde Denis Huseljic Bernhard Sick 28 9 0 05 Apr 2023
SketchBoost: Fast Gradient Boosted Decision Tree for Multioutput Problems L. Iosipoi Anton Vakhrushev 27 7 0 23 Nov 2022
Why do tree-based models still outperform deep learning on tabular data? Léo Grinsztajn Edouard Oyallon Gaël Varoquaux LMTD 35 356 0 18 Jul 2022
Transfer Learning with Deep Tabular Models Roman Levin Valeriia Cherepanova Avi Schwarzschild Arpit Bansal C. Bayan Bruss Tom Goldstein A. Wilson Micah Goldblum OOD FedML LMTD 75 58 0 30 Jun 2022
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 36 647 0 05 Oct 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings Xin Huang A. Khetan Milan Cvitkovic Zohar Karnin ViT LMTD 157 417 0 11 Dec 2020
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data Nick Erickson Jonas W. Mueller Alexander Shirkov Hang Zhang Pedro Larroy Mu Li Alex Smola LMTD 97 607 0 13 Mar 2020
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data Sergei Popov S. Morozov Artem Babenko LMTD 91 294 0 13 Sep 2019