Home  | Tags | #p_kaissis

#p_kaissis

KSR+25

Laplace Sample Information: Data Informativeness Through a Bayesian Lens

ICLR 2025

#p_kaissis #p_rueckert

SKK+25a

Differentially Private Active Learning: Balancing Effective Data Selection and Privacy

SaTML 2025

#p_kaissis

BLS+25

Cross-Domain and Cross-Dimension Learning for Image-to-Graph Transformers

WACV 2025

#p_kaissis #p_menten #p_rueckert

KGK+24

Attack-Aware Noise Calibration for Differential Privacy

Preprint (Nov. 2024)

#p_kaissis

DOR+24

On Differentially Private 3D Medical Image Synthesis With Controllable Latent Diffusion Models

DGM4 @MICCAI 2024

#p_kaissis #p_schnabel

RKZ+24

Complex-Valued Federated Learning With Differential Privacy and MRI Applications

DeCaF @MICCAI 2024

#p_kaissis #p_rueckert #p_schnabel

OLR+24

Enhancing the Utility of Privacy-Preserving Cancer Classification Using Synthetic Data

Deep-Breath @MICCAI 2024

#p_kaissis #p_schnabel

MKR+24

ChEX: Interactive Localization and Region Description in Chest X-Rays

ECCV 2024

#p_kaissis #p_rueckert

UKK24

Memorisation in Machine Learning: A Survey of Results

Transactions on Machine Learning Research. Aug. 2024

#p_kaissis

KKB+24

Beyond the Calibration Point: Mechanism Comparison in Differential Privacy

ICML 2024

#p_kaissis #p_rueckert

ZMS+24

Reconciling Privacy and Accuracy in AI for Medical Imaging

Nature Machine Intelligence 6. Jun. 2024

#p_kaissis #p_rueckert

AZK+24

Preserving Fairness and Diagnostic Accuracy in Private Large-Scale AI Models for Medical Imaging

Communications Medicine 4.46. Mar. 2024

#p_kaissis #p_rueckert

KZK+23

Optimal Privacy Guarantees for a Relaxed Threat Model: Addressing Sub-Optimal Adversaries in Differentially Private Machine Learning

NeurIPS 2023

#p_kaissis #p_rueckert

RKZ+23

Federated Electronic Health Records for the European Health Data Space

The Lancet Digital Health 5.11. Nov. 2023

#p_kaissis #p_rueckert

SKW+22

Relationformer: A Unified Framework for Image-to-Graph Generation

ECCV 2022

#p_kaissis #p_tresp
Back to Top