3 papers
cs.NE2026
An Optimization Framework for Automated Assessment of Biological Plausibility of Spiking Neurons
Sven Nitzsche, Alexandru Ionita, Andreas Faust +2
Biological plausibility is a key concept in neuromorphic computing and spiking neural networks, yet it remains inconsistently defined and difficult to quantify. In this work, we pr…
cs.CR2025
Functional Encryption in Secure Neural Network Training: Data Leakage and Practical Mitigations
Alexandru Ioniţă, Andreea Ioniţă
With the increased interest in artificial intelligence, Machine Learning as a Service provides the infrastructure in the Cloud for easy training, testing, and deploying models. How…
cond-mat.supr-con2020
Superconducting granular aluminum resonators resilient to magnetic fields up to 1 Tesla
K. Borisov, D. Rieger, P. Winkel +8
High kinetic inductance materials constitute a valuable resource for superconducting quantum circuits and hybrid architectures. Superconducting granular aluminum (grAl) reaches kin…