Publications | Jonathan Passerat-Palmbach

2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments

A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification

A blockchain-orchestrated Federated Learning architecture for healthcare consortia

A generic framework for privacy preserving deep learning

Zen and the art of model adaptation: Low-utility-cost attack mitigations in collaborative machine learning

Trust the Process: Zero-Knowledge Machine Learning to Enhance Trust in Generative AI Interactions

Split HE: Fast Secure Inference Combining Split Learning and Homomorphic Encryption

End-to-end privacy preserving deep learning on multi-institutional medical imaging

Cooperative AI via Decentralized Commitment Devices

Contribution Evaluation in Federated Learning: Examining Current Approaches

Adversarial interference and its mitigations in privacy-preserving collaborative machine learning

ARIA: On the interaction between Architectures, Aggregation methods and Initializations in federated visual classification