activity
20162023
most citedReal-time ultra-low power ECG anomaly detection using an event-driven neuromorphic processor

126 citations · 162 across the 7 of their papers we have counts for

collaborators

7 papers

cs.ET2023★ 10 cited

Gradient-descent hardware-aware training and deployment for mixed-signal Neuromorphic processors

Uğurcan Çakal, Maryada, Chenxi Wu +2

Mixed-signal neuromorphic processors provide extremely low-power operation for edge inference workloads, taking advantage of sparse asynchronous computation within Spiking Neural N…

cs.NE2022★ 14 cited

Sub-mW Neuromorphic SNN audio processing applications with Rockpool and Xylo

Hannah Bos, Dylan Muir

Spiking Neural Networks (SNNs) provide an efficient computational mechanism for temporal signal processing, especially when coupled with low-power SNN inference ASICs. SNNs have be…

cs.LG2021★ 3 cited

Network insensitivity to parameter noise via adversarial regularization

Julian Büchel, Fynn Faber, Dylan R. Muir

Neuromorphic neural network processors, in the form of compute-in-memory crossbar arrays of memristors, or in the form of subthreshold analog and mixed-signal ASICs, promise enormo…

cs.LG2021★ 5 cited

Supervised training of spiking neural networks for robust deployment on mixed-signal neuromorphic processors

Julian Büchel, Dmitrii Zendrikov, Sergio Solinas +2

Mixed-signal analog/digital circuits emulate spiking neurons and synapses with extremely high energy efficiency, an approach known as "neuromorphic engineering". However, analog ci…

eess.SP2019★ 126 cited

Real-time ultra-low power ECG anomaly detection using an event-driven neuromorphic processor

Felix Christian Bauer, Dylan Richard Muir, Giacomo Indiveri

Accurate detection of pathological conditions in human subjects can be achieved through off-line analysis of recorded biological signals such as electrocardiograms (ECGs). However,…

cs.NE2017★ 2 cited

Feed-forward approximations to dynamic recurrent network architectures

Dylan Richard Muir

Recurrent neural network architectures can have useful computational properties, with complex temporal dynamics and input-sensitive attractor states. However, evaluation of recurre…

q-bio.NC2016★ 2 cited

Surround suppression explained by long-range recruitment of local competition, in a columnar V1 model

Hongzhi You, Giacomo Indiveri, Dylan Richard Muir

Although neurons in columns of visual cortex of adult carnivores and primates share similar orientation tuning preferences, responses of nearby neurons are surprisingly sparse and…