Dingfan Chen

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 20

Top Topics

State Transition

Gene Expression

Biologically Plausible

Differentially Private

Top Venues

Publications

Derui Zhu, Dingfan Chen, Qing Li, Zongxiong Chen, Lei Ma, Jens Grossklags, Mario Fritz
PoLLMgraph: Unraveling Hallucinations in Large Language Models via State Transition Dynamics. CoRR (2024)
Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations. Proc. Priv. Enhancing Technol. 2024 (3) (2024)
Dingfan Chen, Raouf Kerkouche, Mario Fritz
A Unified View of Differentially Private Deep Generative Modeling. Trans. Mach. Learn. Res. 2024 (2024)
Dingfan Chen, Marie Oestreich, Tejumade Afonja, Raouf Kerkouche, Matthias Becker, Mario Fritz
Towards Biologically Plausible and Private Gene Expression Data Generation. CoRR (2024)
Dingfan Chen, Raouf Kerkouche, Mario Fritz
A Unified View of Differentially Private Deep Generative Modeling. CoRR (2023)
Derui Zhu, Dingfan Chen, Jens Grossklags, Mario Fritz
Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy. CoRR (2023)
Tejumade Afonja, Dingfan Chen, Mario Fritz
MargCTGAN: A "Marginally" Better CTGAN for the Low Sample Regime. CoRR (2023)
Tejumade Afonja, Dingfan Chen, Mario Fritz
MargCTGAN: A "Marginally" Better CTGAN for the Low Sample Regime. DAGM (2023)
Hui-Po Wang, Dingfan Chen, Raouf Kerkouche, Mario Fritz
Fed-GLOSS-DP: Federated, Global Learning using Synthetic Sets with Record Level Differential Privacy. CoRR (2023)
Dingfan Chen, Ning Yu, Mario Fritz
RelaxLoss: Defending Membership Inference Attacks without Losing Utility. CoRR (2022)
Dingfan Chen, Ning Yu, Mario Fritz
RelaxLoss: Defending Membership Inference Attacks without Losing Utility. ICLR (2022)
Dingfan Chen, Raouf Kerkouche, Mario Fritz
Private Set Generation with Discriminative Information. NeurIPS (2022)
Dingfan Chen, Raouf Kerkouche, Mario Fritz
Private Set Generation with Discriminative Information. CoRR (2022)
Ning Yu, Vladislav Skripniuk, Dingfan Chen, Larry S. Davis, Mario Fritz
Responsible Disclosure of Generative Models Using Scalable Fingerprinting. ICLR (2022)
Xiaoyi Chen, Ahmed Salem, Dingfan Chen, Michael Backes, Shiqing Ma, Qingni Shen, Zhonghai Wu, Yang Zhang
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements. ACSAC (2021)
Dingfan Chen, Ning Yu, Yang Zhang, Mario Fritz
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models. CCS (2020)
Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators. CoRR (2020)
Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators. NeurIPS (2020)
Ning Yu, Vladislav Skripniuk, Dingfan Chen, Larry Davis, Mario Fritz
Responsible Disclosure of Generative Models Using Scalable Fingerprinting. CoRR (2020)
Dingfan Chen, Ning Yu, Yang Zhang, Mario Fritz
GAN-Leaks: A Taxonomy of Membership Inference Attacks against GANs. CoRR (2019)