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v1v2 (latest)

Towards a framework on tabular synthetic data generation: a minimalist approach: theory, use cases, and limitations

17 November 2024
Yueyang Shen
Agus Sudjianto
Arun Prakash R
A. Bhattacharyya
Maorong Rao
Yaqun Wang
J. Vaughan
Nengfeng Zhou
ArXiv (abs)PDFHTML

Papers citing "Towards a framework on tabular synthetic data generation: a minimalist approach: theory, use cases, and limitations"

14 / 14 papers shown
Title
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
140
699
0
05 Oct 2021
Understanding How Dimension Reduction Tools Work: An Empirical Approach
  to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
Yingfan Wang
Haiyang Huang
Cynthia Rudin
Yaron Shaposhnik
251
316
0
08 Dec 2020
Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and
  Survey
Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey
Benyamin Ghojogh
A. Ghodsi
Fakhri Karray
Mark Crowley
54
29
0
17 Sep 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
923
42,569
0
28 May 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
658
4,931
0
23 Jan 2020
UMAP: Uniform Manifold Approximation and Projection for Dimension
  Reduction
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Leland McInnes
John Healy
James Melville
221
9,502
0
09 Feb 2018
A Note on the Inception Score
A Note on the Inception Score
Shane T. Barratt
Rishi Sharma
EGVM
110
695
0
06 Jan 2018
Masked Autoregressive Flow for Density Estimation
Masked Autoregressive Flow for Density Estimation
George Papamakarios
Theo Pavlakou
Iain Murray
231
1,360
0
19 May 2017
XGBoost: A Scalable Tree Boosting System
XGBoost: A Scalable Tree Boosting System
Tianqi Chen
Carlos Guestrin
827
39,269
0
09 Mar 2016
Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende
S. Mohamed
DRLBDL
332
4,200
0
21 May 2015
Deep Learning and the Information Bottleneck Principle
Deep Learning and the Information Bottleneck Principle
Naftali Tishby
Noga Zaslavsky
DRL
220
1,595
0
09 Mar 2015
MADE: Masked Autoencoder for Distribution Estimation
MADE: Masked Autoencoder for Distribution Estimation
M. Germain
Karol Gregor
Iain Murray
Hugo Larochelle
OODSyDaUQCV
193
874
0
12 Feb 2015
A Convolutional Neural Network for Modelling Sentences
A Convolutional Neural Network for Modelling Sentences
Nal Kalchbrenner
Edward Grefenstette
Phil Blunsom
116
3,563
0
08 Apr 2014
Testing the Manifold Hypothesis
Testing the Manifold Hypothesis
Charles Fefferman
S. Mitter
Hariharan Narayanan
170
537
0
01 Oct 2013
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