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

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

2 June 2021
Gowthami Somepalli
Micah Goldblum
Avi Schwarzschild
C. Bayan Bruss
Tom Goldstein
    LMTD
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Papers citing "SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training"

5 / 55 papers shown
Title
On Embeddings for Numerical Features in Tabular Deep Learning
On Embeddings for Numerical Features in Tabular Deep Learning
Yura Gorishniy
Ivan Rubachev
Artem Babenko
LMTD
18
157
0
10 Mar 2022
Robbing the Fed: Directly Obtaining Private Data in Federated Learning
  with Modified Models
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
Deep Neural Networks and Tabular Data: A Survey
Deep Neural Networks and Tabular Data: A Survey
V. Borisov
Tobias Leemann
Kathrin Seßler
Johannes Haug
Martin Pawelczyk
Gjergji Kasneci
LMTD
47
650
0
05 Oct 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
Xin Huang
A. Khetan
Milan Cvitkovic
Zohar Karnin
ViT
LMTD
157
420
0
11 Dec 2020
AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data
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
612
0
13 Mar 2020
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