Large-scale numerical simulations of detailed brain circuit models are important for
identifying hypotheses on brain functions and testing their consistency and plausibility. An …

We derive the mean-field equations arising as the limit of a network of interacting spiking
neurons, as the number of neurons goes to infinity. The neurons belong to a fixed number of …

Homomorphic encryption (HE) offers great capabilities that can solve a wide range of
privacy-preserving computing problems. This tool allows anyone to process encrypted data …

As a major breakthrough, in 2009 Gentry introduced the first plausible construction of a fully
homomorphic encryption (FHE) scheme. FHE allows the evaluation of arbitrary functions …

In 2010, Gentry and Halevi presented the first FHE implementation. FHE allows the
evaluation of arbitrary functions directly on encrypted data on untrusted servers. However …

Analysis of functional magnetic resonance imaging (fMRI) data is becoming ever more
computationally demanding as temporal and spatial resolutions improve, and large, publicly …

As the desire for biologically realistic spiking neural networks (SNNs) increases, tuning the
enormous number of open parameters in these models becomes a difficult challenge. SNNs …

Graphical processing units (GPUs) can significantly accelerate spiking neural network
(SNN) simulations by exploiting parallelism for independent computations. Both the changes …

A new approach to perform analog optical differentiation is presented using half-wavelength
slabs. First, a half-wavelength dielectric slab is used to design a first order differentiator. The …

This paper proposes a strategy for the efficient implementation of Fixed Grid Finite Element
Analysis (FGFEA) method on Graphics Processing Units (GPUs). Such a strategy makes use …