ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2206.15306
  4. Cited By
Transfer Learning with Deep Tabular Models
v1v2 (latest)

Transfer Learning with Deep Tabular Models

30 June 2022
Roman Levin
Valeriia Cherepanova
Avi Schwarzschild
Arpit Bansal
C. Bayan Bruss
Tom Goldstein
A. Wilson
Micah Goldblum
    OODFedMLLMTD
ArXiv (abs)PDFHTMLGithub (103★)

Papers citing "Transfer Learning with Deep Tabular Models"

50 / 52 papers shown
Title
TabSTAR: A Foundation Tabular Model With Semantically Target-Aware Representations
Alan Arazi
Eilam Shapira
Roi Reichart
LMTD
190
0
0
23 May 2025
Revisiting Pretraining Objectives for Tabular Deep Learning
Revisiting Pretraining Objectives for Tabular Deep Learning
Ivan Rubachev
Artem Alekberov
Yu. V. Gorishniy
Artem Babenko
LMTD
56
47
0
07 Jul 2022
Hopular: Modern Hopfield Networks for Tabular Data
Hopular: Modern Hopfield Networks for Tabular Data
Bernhard Schafl
Lukas Gruber
Angela Bitto-Nemling
Sepp Hochreiter
LMTD
66
28
0
01 Jun 2022
TransTab: Learning Transferable Tabular Transformers Across Tables
TransTab: Learning Transferable Tabular Transformers Across Tables
Zifeng Wang
Jimeng Sun
LMTD
68
147
0
19 May 2022
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
103
177
0
10 Mar 2022
Consolidated learning -- a domain-specific model-free optimization
  strategy with examples for XGBoost and MIMIC-IV
Consolidated learning -- a domain-specific model-free optimization strategy with examples for XGBoost and MIMIC-IV
Katarzyna Wo'znica
Mateusz Grzyb
Zuzanna Trafas
P. Biecek
106
2
0
27 Jan 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViTTPM
477
7,819
0
11 Nov 2021
SubTab: Subsetting Features of Tabular Data for Self-Supervised
  Representation Learning
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
Talip Uçar
Ehsan Hajiramezanali
Lindsay Edwards
LMTDSSL
66
133
0
08 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
112
697
0
05 Oct 2021
Simple Modifications to Improve Tabular Neural Networks
Simple Modifications to Improve Tabular Neural Networks
J. Fiedler
LMTD
117
19
0
06 Aug 2021
SCARF: Self-Supervised Contrastive Learning using Random Feature
  Corruption
SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption
Dara Bahri
Heinrich Jiang
Yi Tay
Donald Metzler
SSL
70
175
0
29 Jun 2021
Revisiting Deep Learning Models for Tabular Data
Revisiting Deep Learning Models for Tabular Data
Yu. V. Gorishniy
Ivan Rubachev
Valentin Khrulkov
Artem Babenko
LMTD
122
765
0
22 Jun 2021
Locally Sparse Neural Networks for Tabular Biomedical Data
Locally Sparse Neural Networks for Tabular Biomedical Data
Junchen Yang
Ofir Lindenbaum
Y. Kluger
58
34
0
11 Jun 2021
Neighborhood Contrastive Learning Applied to Online Patient Monitoring
Neighborhood Contrastive Learning Applied to Online Patient Monitoring
Hugo Yèche
Gideon Dresdner
Francesco Locatello
Matthias Huser
Gunnar Rätsch
69
48
0
09 Jun 2021
CoAtNet: Marrying Convolution and Attention for All Data Sizes
CoAtNet: Marrying Convolution and Attention for All Data Sizes
Zihang Dai
Hanxiao Liu
Quoc V. Le
Mingxing Tan
ViT
132
1,208
0
09 Jun 2021
Tabular Data: Deep Learning is Not All You Need
Tabular Data: Deep Learning is Not All You Need
Ravid Shwartz-Ziv
Amitai Armon
LMTD
159
1,275
0
06 Jun 2021
Self-Attention Between Datapoints: Going Beyond Individual Input-Output
  Pairs in Deep Learning
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning
Jannik Kossen
Neil Band
Clare Lyle
Aidan Gomez
Tom Rainforth
Y. Gal
OOD3DPC
103
141
0
04 Jun 2021
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
Gowthami Somepalli
Micah Goldblum
Avi Schwarzschild
C. Bayan Bruss
Tom Goldstein
LMTD
88
331
0
02 Jun 2021
VICReg: Variance-Invariance-Covariance Regularization for
  Self-Supervised Learning
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning
Adrien Bardes
Jean Ponce
Yann LeCun
SSLDML
153
944
0
11 May 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
Xin Huang
A. Khetan
Milan Cvitkovic
Zohar Karnin
ViTLMTD
207
457
0
11 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
673
41,430
0
22 Oct 2020
Unsupervised Learning of Visual Features by Contrasting Cluster
  Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCLSSL
264
4,098
0
17 Jun 2020
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data
Pengcheng Yin
Graham Neubig
Wen-tau Yih
Sebastian Riedel
RALMLMTD
94
605
0
17 May 2020
Joint Liver Lesion Segmentation and Classification via Transfer Learning
Joint Liver Lesion Segmentation and Classification via Transfer Learning
Michal Heker
H. Greenspan
MedIm
77
34
0
26 Apr 2020
Adapted tree boosting for Transfer Learning
Adapted tree boosting for Transfer Learning
Wenjing Fang
Chaochao Chen
Bowen Song
Li Wang
Jun Zhou
Kenny Q. Zhu
34
13
0
27 Feb 2020
Gradient Boosting Neural Networks: GrowNet
Gradient Boosting Neural Networks: GrowNet
Sarkhan Badirli
Xuanqing Liu
Zhengming Xing
Avradeep Bhowmik
Khoa D. Doan
S. Keerthi
FedML
56
87
0
19 Feb 2020
The Tree Ensemble Layer: Differentiability meets Conditional Computation
The Tree Ensemble Layer: Differentiability meets Conditional Computation
Hussein Hazimeh
Natalia Ponomareva
P. Mol
Zhenyu Tan
Rahul Mazumder
UQCVAI4CE
392
80
0
18 Feb 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
387
18,866
0
13 Feb 2020
Self-Supervised Learning of Pretext-Invariant Representations
Self-Supervised Learning of Pretext-Invariant Representations
Ishan Misra
Laurens van der Maaten
SSLVLM
108
1,458
0
04 Dec 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
213
12,124
0
13 Nov 2019
A Comprehensive Survey on Transfer Learning
A Comprehensive Survey on Transfer Learning
Fuzhen Zhuang
Zhiyuan Qi
Keyu Duan
Dongbo Xi
Yongchun Zhu
Hengshu Zhu
Hui Xiong
Qing He
186
4,471
0
07 Nov 2019
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language
  Generation, Translation, and Comprehension
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
M. Lewis
Yinhan Liu
Naman Goyal
Marjan Ghazvininejad
Abdel-rahman Mohamed
Omer Levy
Veselin Stoyanov
Luke Zettlemoyer
AIMatVLM
264
10,851
0
29 Oct 2019
ALBERT: A Lite BERT for Self-supervised Learning of Language
  Representations
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan
Mingda Chen
Sebastian Goodman
Kevin Gimpel
Piyush Sharma
Radu Soricut
SSLAIMat
373
6,467
0
26 Sep 2019
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
Sergei Popov
S. Morozov
Artem Babenko
LMTD
148
317
0
13 Sep 2019
TabNet: Attentive Interpretable Tabular Learning
TabNet: Attentive Interpretable Tabular Learning
Sercan O. Arik
Tomas Pfister
LMTD
206
1,355
0
20 Aug 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu
Myle Ott
Naman Goyal
Jingfei Du
Mandar Joshi
Danqi Chen
Omer Levy
M. Lewis
Luke Zettlemoyer
Veselin Stoyanov
AIMat
680
24,541
0
26 Jul 2019
Optuna: A Next-generation Hyperparameter Optimization Framework
Optuna: A Next-generation Hyperparameter Optimization Framework
Takuya Akiba
Shotaro Sano
Toshihiko Yanase
Takeru Ohta
Masanori Koyama
668
5,839
0
25 Jul 2019
CutMix: Regularization Strategy to Train Strong Classifiers with
  Localizable Features
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features
Sangdoo Yun
Dongyoon Han
Seong Joon Oh
Sanghyuk Chun
Junsuk Choe
Y. Yoo
OOD
622
4,802
0
13 May 2019
Med3D: Transfer Learning for 3D Medical Image Analysis
Med3D: Transfer Learning for 3D Medical Image Analysis
Sihong Chen
Kai Ma
Yefeng Zheng
MedIm
64
464
0
01 Apr 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and
  Expert Comparison
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
Jeremy Irvin
Pranav Rajpurkar
M. Ko
Yifan Yu
Silviana Ciurea-Ilcus
...
D. Larson
C. Langlotz
Bhavik Patel
M. Lungren
A. Ng
116
2,601
0
21 Jan 2019
AutoInt: Automatic Feature Interaction Learning via Self-Attentive
  Neural Networks
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
Weiping Song
Chence Shi
Zhiping Xiao
Zhijian Duan
Yewen Xu
Ming Zhang
Jian Tang
CML
87
857
0
29 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language
  Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin
Ming-Wei Chang
Kenton Lee
Kristina Toutanova
VLMSSLSSeg
1.8K
95,175
0
11 Oct 2018
Deep Neural Decision Trees
Deep Neural Decision Trees
Yongxin Yang
Irene Garcia Morillo
Timothy M. Hospedales
PINN
53
186
0
19 Jun 2018
GAIN: Missing Data Imputation using Generative Adversarial Nets
GAIN: Missing Data Imputation using Generative Adversarial Nets
Jinsung Yoon
James Jordon
M. Schaar
GAN
63
1,026
0
07 Jun 2018
YOLOv3: An Incremental Improvement
YOLOv3: An Incremental Improvement
Joseph Redmon
Ali Farhadi
ObjD
130
21,482
0
08 Apr 2018
Encoder-Decoder with Atrous Separable Convolution for Semantic Image
  Segmentation
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Liang-Chieh Chen
Yukun Zhu
George Papandreou
Florian Schroff
Hartwig Adam
SSeg
480
13,178
0
07 Feb 2018
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
289
9,803
0
25 Oct 2017
Deep & Cross Network for Ad Click Predictions
Deep & Cross Network for Ad Click Predictions
Ruoxi Wang
Bin Fu
Gang Fu
Mingliang Wang
104
1,234
0
17 Aug 2017
Self-Normalizing Neural Networks
Self-Normalizing Neural Networks
Günter Klambauer
Thomas Unterthiner
Andreas Mayr
Sepp Hochreiter
470
2,519
0
08 Jun 2017
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
814
39,062
0
09 Mar 2016
12
Next