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Daniel Rueckert — most-cited papers & profile · Federated Learning
← authors
·
overview
Daniel Rueckert
30
papers ·
663
citations ·
132
h-index
University Medical Center Utrecht · Munich Center for Machine Learning · Imperial College London · Technical University of Munich
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Most-cited papers
A generic framework for privacy preserving deep learning
2018 · 342 citations
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
2020 · 28 citations
Personalized Federated Deep Learning for Pain Estimation From Face Images
2021 · 18 citations
FedNorm: Modality-Based Normalization in Federated Learning for Multi-Modal Liver Segmentation
2022 · 16 citations
2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments
2020 · 10 citations
Privacy-preserving medical image analysis
2020 · 7 citations
FedDis: Disentangled Federated Learning for Unsupervised Brain Pathology Segmentation
2021 · 7 citations
Complex-valued Federated Learning with Differential Privacy and MRI Applications
2021 · 6 citations
HyFed: A Hybrid Federated Framework for Privacy-preserving Machine Learning
2021 · 3 citations
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks
2022 · 3 citations
Differentially private federated deep learning for multi-site medical image segmentation
2021 · 2 citations
FedRAD: Federated Robust Adaptive Distillation
2021 · 1 citations
Kernel Normalized Convolutional Networks for Privacy-Preserving Machine Learning
2022 · 1 citations
Distributed Machine Learning and the Semblance of Trust
2021
Can collaborative learning be private, robust and scalable?
2022
Top co-authors
Georgios Kaissis
· 9
Dmitrii Usynin
· 6
Alexander Ziller
· 4
Jonathan Passerat-Palmbach
· 4
Amir Alansary
· 2
Andrew Trask
· 2
Jason Mancuso
· 2
Jonathan Passerat‐Palmbach
· 2
Luis Mu\~noz-Gonz\'alez
· 2
Marcus Makowski
· 2
Matei Grama
· 2
Reza Nasirigerdeh
· 2
Topics
Federated Learning
Privacy
Security
Adversarial Attacks
Data Heterogeneity
Optimization
Encryption