Eric Jahns
Orcid: 0009-0004-5511-7975
According to our database1,
Eric Jahns authored at least 11 papers
between 2025 and 2026.
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Bibliography
2026
Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networks.
CoRR, April, 2026
SentinelTouch: A Lightweight Privacy-Preserving Biometric-Fingerprinting Authentication and Identification System Based on Neural Networks and Homomorphic Encryption.
Proc. Priv. Enhancing Technol., 2026
2025
CoRR, October, 2025
Discretized Quadratic Integrate-and-Fire Neuron Model for Deep Spiking Neural Networks.
CoRR, October, 2025
FHEON: A Configurable Framework for Developing Privacy-Preserving Neural Networks Using Homomorphic Encryption.
CoRR, October, 2025
PrivSpike: Employing Homomorphic Encryption for Private Inference of Deep Spiking Neural Networks.
CoRR, October, 2025
GuardianML: Anatomy of Privacy-Preserving Machine Learning Techniques and Frameworks.
IEEE Access, 2025
Privacy-Preserving Deep Learning: A Survey on Theoretical Foundations, Software Frameworks, and Hardware Accelerators.
IEEE Access, 2025
R-Visor: An Extensible Dynamic Binary Instrumentation and Analysis Framework for Open Instruction Set Architectures.
Proceedings of the 26th ACM SIGPLAN/SIGBED International Conference on Languages, 2025
AQUILA: A Flexible Architecture Guideline for Building Custom Distributed Systems Testbeds.
Proceedings of the 23rd IEEE International Conference on Embedded and Ubiquitous Computing, 2025