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. 2305.09235
  4. Cited By
Synthetic data, real errors: how (not) to publish and use synthetic data

Synthetic data, real errors: how (not) to publish and use synthetic data

16 May 2023
B. V. Breugel
Zhaozhi Qian
M. Schaar
    SyDa
ArXivPDFHTML

Papers citing "Synthetic data, real errors: how (not) to publish and use synthetic data"

11 / 11 papers shown
Title
Debiasing Synthetic Data Generated by Deep Generative Models
Debiasing Synthetic Data Generated by Deep Generative Models
A. Decruyenaere
Heidelinde Dehaene
Paloma Rabaey
Christiaan Polet
Johan Decruyenaere
Thomas Demeester
S. Vansteelandt
AI4CE
21
0
0
06 Nov 2024
Montessori-Instruct: Generate Influential Training Data Tailored for
  Student Learning
Montessori-Instruct: Generate Influential Training Data Tailored for Student Learning
Xiaochuan Li
Zichun Yu
Chenyan Xiong
SyDa
27
1
0
18 Oct 2024
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets
Ossi Raisa
Antti Honkela
67
0
0
06 Feb 2024
Generative Semi-supervised Learning with Meta-Optimized Synthetic
  Samples
Generative Semi-supervised Learning with Meta-Optimized Synthetic Samples
Shinýa Yamaguchi
19
2
0
28 Sep 2023
On Consistent Bayesian Inference from Synthetic Data
On Consistent Bayesian Inference from Synthetic Data
Ossi Raisa
Joonas Jälkö
Antti Honkela
SyDa
11
2
0
26 May 2023
Utility Theory of Synthetic Data Generation
Utility Theory of Synthetic Data Generation
Shi Xu
W. Sun
Guang Cheng
10
5
0
17 May 2023
Conditional Synthetic Data Generation for Robust Machine Learning
  Applications with Limited Pandemic Data
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data
Hari Prasanna Das
Ryan Tran
Japjot Singh
Xiangyu Yue
G. Tison
Alberto L. Sangiovanni-Vincentelli
C. Spanos
OOD
MedIm
50
51
0
14 Sep 2021
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating
  and Auditing Generative Models
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models
Ahmed Alaa
B. V. Breugel
Evgeny S. Saveliev
M. Schaar
38
186
0
17 Feb 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
SMOTE: Synthetic Minority Over-sampling Technique
SMOTE: Synthetic Minority Over-sampling Technique
Nitesh V. Chawla
Kevin W. Bowyer
Lawrence Hall
W. Kegelmeyer
AI4TS
154
25,150
0
09 Jun 2011
1