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A Unified View of Differentially Private Deep Generative Modeling

A Unified View of Differentially Private Deep Generative Modeling

27 September 2023
Dingfan Chen
Raouf Kerkouche
Mario Fritz
    SyDa
ArXivPDFHTML

Papers citing "A Unified View of Differentially Private Deep Generative Modeling"

11 / 11 papers shown
Title
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong
Kecen Li
Zinan Lin
Tianhao Wang
47
3
0
18 Mar 2025
Advancing Retail Data Science: Comprehensive Evaluation of Synthetic
  Data
Advancing Retail Data Science: Comprehensive Evaluation of Synthetic Data
Yu Xia
Chi-Hua Wang
Joshua Mabry
Guang Cheng
ELM
32
3
0
19 Jun 2024
PrivImage: Differentially Private Synthetic Image Generation using
  Diffusion Models with Semantic-Aware Pretraining
PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining
Kecen Li
Chen Gong
Zhixiang Li
Yuzhong Zhao
Xinwen Hou
Tianhao Wang
23
10
0
19 Oct 2023
How to DP-fy ML: A Practical Guide to Machine Learning with Differential
  Privacy
How to DP-fy ML: A Practical Guide to Machine Learning with Differential Privacy
Natalia Ponomareva
Hussein Hazimeh
Alexey Kurakin
Zheng Xu
Carson E. Denison
H. B. McMahan
Sergei Vassilvitskii
Steve Chien
Abhradeep Thakurta
94
167
0
01 Mar 2023
Differentially Private Generative Adversarial Networks with Model
  Inversion
Differentially Private Generative Adversarial Networks with Model Inversion
Dongjie Chen
S. Cheung
Chen-Nee Chuah
Sally Ozonoff
SyDa
13
13
0
10 Jan 2022
Differentially Private Fine-tuning of Language Models
Differentially Private Fine-tuning of Language Models
Da Yu
Saurabh Naik
A. Backurs
Sivakanth Gopi
Huseyin A. Inan
...
Y. Lee
Andre Manoel
Lukas Wutschitz
Sergey Yekhanin
Huishuai Zhang
134
344
0
13 Oct 2021
Robin Hood and Matthew Effects: Differential Privacy Has Disparate
  Impact on Synthetic Data
Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data
Georgi Ganev
Bristena Oprisanu
Emiliano De Cristofaro
37
57
0
23 Sep 2021
FedDPGAN: Federated Differentially Private Generative Adversarial
  Networks Framework for the Detection of COVID-19 Pneumonia
FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumonia
Longling Zhang
Bochen Shen
A. Barnawi
Shan Xi
Neeraj Kumar
Yi Wu
FedML
MedIm
71
80
0
26 Apr 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
40
186
0
17 Feb 2021
Conditional Image Synthesis With Auxiliary Classifier GANs
Conditional Image Synthesis With Auxiliary Classifier GANs
Augustus Odena
C. Olah
Jonathon Shlens
GAN
224
3,183
0
30 Oct 2016
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
225
2,543
0
25 Jan 2016
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