63 citations · 122 across the 8 of their papers we have counts for
8 papers
SEPhIA: <1 laser/neuron Spiking Electro-Photonic Integrated Multi-Tiled Architecture for Scalable Optical Neuromorphic Computing
Matěj Hejda, Aishwarya Natarajan, Chaerin Hong +4
Research into optical spiking neural networks (SNNs) has primarily focused on spiking devices, networks of excitable lasers or numerical modelling of large architectures, often ove…
A More Convex Ising Formulation of Max-3-Cut Using Higher-Order Spin Interactions
Robbe De Prins, Guy Van der Sande, Peter Bienstman +1
Many combinatorial optimization problems (COPs) are naturally expressed using variables that take on more than two discrete values. To solve such problems using Ising machines (IMs…
How to Incorporate Higher-order Interactions in Analog Ising Machines
Robbe De Prins, Guy Van der Sande, Peter Bienstman +1
Ising machines (IMs) are specialized devices designed to efficiently solve combinatorial optimization problems. Among such problems, Boolean Satisfiability (SAT) is particularly re…
Roadmap on Neuromorphic Photonics
Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147
This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…
NEUROPULS: NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS
Fabio Pavanello, Cedric Marchand, Ian O'Connor +34
This special session paper introduces the Horizon Europe NEUROPULS project, which targets the development of secure and energy-efficient RISC-V interfaced neuromorphic accelerators…
Special Session: Neuromorphic hardware design and reliability from traditional CMOS to emerging technologies
Fabio Pavanello, Elena Ioana Vatajelu, Alberto Bosio +6
The field of neuromorphic computing has been rapidly evolving in recent years, with an increasing focus on hardware design and reliability. This special session paper provides an o…
Order-of-magnitude differences in computational performance of analog Ising machines induced by the choice of nonlinearity
Fabian Böhm, Thomas Van Vaerenbergh, Guy Verschaffelt +1
Ising machines based on nonlinear analog systems are a promising method to accelerate computation of NP-hard optimization problems. Yet, their analog nature is also causing amplitu…
Harnessing Intrinsic Noise in Memristor Hopfield Neural Networks for Combinatorial Optimization
Fuxi Cai, Suhas Kumar, Thomas Van Vaerenbergh +8
We describe a hybrid analog-digital computing approach to solve important combinatorial optimization problems that leverages memristors (two-terminal nonvolatile memories). While p…