1.1k citations · 4.6k across the 68 of their papers we have counts for
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Stochastic Interpretation of Quasi-periodic Event-based Systems
Hesham Mostafa, Giacomo Indiveri
Many networks used in machine learning and as models of biological neural networks make use of stochastic neurons or neuron-like units. We show that stochastic artificial neurons c…
Spiking Analog VLSI Neuron Assemblies as Constraint Satisfaction Problem Solvers
Jonathan Binas, Giacomo Indiveri, Michael Pfeiffer
Solving constraint satisfaction problems (CSPs) is a notoriously expensive computational task. Recently, it has been proposed that efficient stochastic solvers can be obtained thro…
Emulating short-term synaptic dynamics with memristive devices
Radu Berdan, Eleni Vasilaki, Ali Khiat +3
Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are h…
Memory and information processing in neuromorphic systems
Giacomo Indiveri, Shih-Chii Liu
A striking difference between brain-inspired neuromorphic processors and current von Neumann processors architectures is the way in which memory and processing is organized. As Inf…
An event-based architecture for solving constraint satisfaction problems
Hesham Mostafa, Lorenz K. Müller, Giacomo Indiveri
Constraint satisfaction problems (CSPs) are typically solved using conventional von Neumann computing architectures. However, these architectures do not reflect the distributed nat…
Rounding Methods for Neural Networks with Low Resolution Synaptic Weights
Lorenz K. Muller, Giacomo Indiveri
Neural network algorithms simulated on standard computing platforms typically make use of high resolution weights, with floating-point notation. However, for dedicated hardware imp…