SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

2 June 2021

Papers citing "SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training"

50 / 53 papers shown

Title
Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Ruxue Shi Hengrui Gu Xu Shen Xin Wang LMTD 193 0 0 09 May 2025
Griffin: Towards a Graph-Centric Relational Database Foundation Model Yanbo Wang Xiyuan Wang Quan Gan Minjie Wang Qibin Yang David Wipf Muhan Zhang 109 0 0 08 May 2025
Attention-enabled Explainable AI for Bladder Cancer Recurrence Prediction Saram Abbas Naeem Soomro R. Shafik Rakesh Heer Kabita Adhikari 51 0 0 30 Apr 2025
ALF: Advertiser Large Foundation Model for Multi-Modal Advertiser Understanding Santosh Rajagopalan Jonathan Vronsky Songbai Yan S. Alireza Golestaneh Shubhra Chandra Min Zhou 66 0 0 26 Apr 2025
TabKAN: Advancing Tabular Data Analysis using Kolmogorov-Arnold Network Ali Eslamian Alireza Afzal Aghaei Qiang Cheng LMTD 82 0 0 09 Apr 2025
STiL: Semi-supervised Tabular-Image Learning for Comprehensive Task-Relevant Information Exploration in Multimodal Classification Siyi Du Xinzhe Luo D. O’Regan Chen Qin 69 0 0 08 Mar 2025
Large Language Models as Attribution Regularizers for Efficient Model Training Davor Vukadin Marin Šilić Goran Delač 41 0 0 27 Feb 2025
Imputation for prediction: beware of diminishing returns Marine Le Morvan Gaël Varoquaux AI4TS 78 1 0 21 Feb 2025
Tabular Embeddings for Tables with Bi-Dimensional Hierarchical Metadata and Nesting Gyanendra Shrestha Chutain Jiang Sai Akula Vivek Yannam Anna Pyayt Michael Gubanov LMTD 97 0 0 20 Feb 2025
Zero-Shot Decision Tree Construction via Large Language Models Lucas Carrasco Felipe Urrutia Andrés Abeliuk 63 0 0 28 Jan 2025
TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling Yury Gorishniy Akim Kotelnikov Artem Babenko LMTD MoE 94 6 0 31 Oct 2024
T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data Hugo Thimonier José Lucas De Melo Costa Fabrice Popineau Arpad Rimmel Bich-Liên Doan 53 1 0 07 Oct 2024
Challenging Gradient Boosted Decision Trees with Tabular Transformers for Fraud Detection at Booking.com Sergei Krutikov Bulat Khaertdinov Rodion Kiriukhin Shubham Agrawal Kees Jan de Vries LMTD 48 0 0 22 May 2024
A Comprehensive Survey on Data Augmentation Zaitian Wang Pengfei Wang Kunpeng Liu Pengyang Wang Yanjie Fu Chang-Tien Lu Charu Aggarwal Jian Pei Yuanchun Zhou ViT 109 22 0 15 May 2024
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey Xi Fang Weijie Xu Fiona Anting Tan Jiani Zhang Ziqing Hu Yanjun Qi Scott Nickleach Diego Socolinsky Srinivasan H. Sengamedu Christos Faloutsos LMTD ALM 42 66 0 27 Feb 2024
CARTE: Pretraining and Transfer for Tabular Learning Myung Jun Kim Léo Grinsztajn Gaël Varoquaux LMTD 62 13 0 26 Feb 2024
HyperFast: Instant Classification for Tabular Data David Bonet D. M. Montserrat Xavier Giró-i-Nieto A. Ioannidis 46 15 0 22 Feb 2024
A Survey on Self-Supervised Learning for Non-Sequential Tabular Data Wei-Yao Wang Wei-Wei Du Derek Xu Wei Wang Wenjie Peng LMTD 38 7 0 02 Feb 2024
DoubleMLDeep: Estimation of Causal Effects with Multimodal Data Jan Rabenseifner Jan Teichert-Kluge Philipp Bach Victor Chernozhukov Martin Spindler Suhas Vijaykumar BDL CML 18 6 0 01 Feb 2024
Towards a Foundation Purchasing Model: Pretrained Generative Autoregression on Transaction Sequences Piotr Skalski David Sutton Stuart Burrell Iker Perez Jason Wong AI4TS 42 2 0 03 Jan 2024
Polynomial-based Self-Attention for Table Representation learning Jayoung Kim Yehjin Shin Jeongwhan Choi Hyowon Wi Noseong Park LMTD 27 2 0 12 Dec 2023
Comparative Analysis of Transformers for Modeling Tabular Data: A Casestudy using Industry Scale Dataset Usneek Singh Piyush Arora Shamika Ganesan Mohit Kumar Siddhant Kulkarni Salil R. Joshi 61 2 0 24 Nov 2023
Scaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks Ben Feuer Chinmay Hegde Niv Cohen 37 10 0 17 Nov 2023
On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series Rita Kuznetsova Alizée Pace Manuel Burger Hugo Yèche Gunnar Rätsch AI4TS 39 5 0 15 Nov 2023
Learning Interpretable Rules for Scalable Data Representation and Classification Zhuo Wang Wei Zhang Ning Liu Jianyong Wang 30 6 0 22 Oct 2023
Survey on Imbalanced Data, Representation Learning and SEP Forecasting Josias Moukpe AI4TS 27 0 0 11 Oct 2023
UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science Yazheng Yang Yuqi Wang Guangyi Liu Ledell Yu Wu Qi Liu LMTD 32 16 0 18 Jul 2023
Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics Kenta Oono Nontawat Charoenphakdee K. Bito Zhengyan Gao Yoshiaki Ota ... Kohei Hayashi Yuki Saito Koki Tsuda Hiroshi Maruyama K. Hayashi 32 1 0 19 Jun 2023
$Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph$ Enabling tabular deep learning when $d \gg n$ with an auxiliary knowledge graph Camilo Ruiz Hongyu Ren Kexin Huang J. Leskovec 25 2 0 07 Jun 2023
Gemtelligence: Accelerating Gemstone classification with Deep Learning Tommaso Bendinelli Luca Biggio D. Nyfeler Abhigyan Ghosh P. Tollan M. Kirschmann Olga Fink 25 1 0 31 May 2023
MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement Zifeng Wang Chufan Gao Cao Xiao Jimeng Sun LMTD 28 12 0 20 May 2023
Self-Reinforcement Attention Mechanism For Tabular Learning Kodjo Mawuena Amekoe M. Dilmi Hanene Azzag M. Lebbah Zaineb Chelly Dagdia Gregoire Jaffre 43 0 0 19 May 2023
Rethinking Data Augmentation for Tabular Data in Deep Learning Soma Onishi Shoya Meguro LMTD 26 14 0 17 May 2023
LEURN: Learning Explainable Univariate Rules with Neural Networks Çağlar Aytekin FAtt 29 0 0 27 Mar 2023
STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables Jaehyun Nam Jihoon Tack Kyungmin Lee Hankook Lee Jinwoo Shin LMTD SSL 21 31 0 02 Mar 2023
Embeddings for Tabular Data: A Survey Rajat Singh Srikanta J. Bedathur LMTD 37 2 0 23 Feb 2023
One Transformer for All Time Series: Representing and Training with Time-Dependent Heterogeneous Tabular Data Simone Luetto Fabrizio Garuti E. Sangineto L. Forni Rita Cucchiara LMTD AI4TS 87 10 0 13 Feb 2023
Local Contrastive Feature learning for Tabular Data Zhabiz Gharibshah Xingquan Zhu SSL 18 7 0 19 Nov 2022
The Missing Indicator Method: From Low to High Dimensions Mike Van Ness Tomas M. Bosschieter Roberto Halpin-Gregorio Madeleine Udell AI4TS 27 15 0 16 Nov 2022
Flaky Performances when Pretraining on Relational Databases Shengchao Liu David Vazquez Jian Tang Pierre-Andre Noel 31 2 0 09 Nov 2022
Realistic Data Augmentation Framework for Enhancing Tabular Reasoning D. K. Santhosh Kumar Vivek Gupta Soumya Sharma Shuo Zhang LMTD 21 3 0 23 Oct 2022
TabLLM: Few-shot Classification of Tabular Data with Large Language Models S. Hegselmann Alejandro Buendia Hunter Lang Monica Agrawal Xiaoyi Jiang David Sontag LMTD 55 211 0 19 Oct 2022
Language Models are Realistic Tabular Data Generators V. Borisov Kathrin Seßler Tobias Leemann Martin Pawelczyk Gjergji Kasneci LMTD 27 223 0 12 Oct 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
Revisiting Pretraining Objectives for Tabular Deep Learning Ivan Rubachev Artem Alekberov Yu. V. Gorishniy Artem Babenko LMTD 21 41 0 07 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
TransTab: Learning Transferable Tabular Transformers Across Tables Zifeng Wang Jimeng Sun LMTD 36 137 0 19 May 2022
Perturbation of Deep Autoencoder Weights for Model Compression and Classification of Tabular Data Manar D. Samad Sakib Abrar 22 12 0 17 May 2022
On Embeddings for Numerical Features in Tabular Deep Learning Yura Gorishniy Ivan Rubachev Artem Babenko LMTD 13 156 0 10 Mar 2022
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models Liam H. Fowl Jonas Geiping W. Czaja Micah Goldblum Tom Goldstein FedML 38 145 0 25 Oct 2021