tag: SNNs

ReRAM-based Neo-Hebbian Synapses For Training Neuromorphic HW (IIT Madras, UCSB)
By Technical Paper Link - 23 Feb, 2026 - Comments: 0

A new technical paper, "NeoHebbian synapses to accelerate online training of neuromorphic hardware," was published by researchers at IIT Madras and UC Santa Barbara. Abstract "Neuromorphic systems that employ advanced synaptic learning rules, such as the three-factor learning rule, require synaptic devices of increased complexity. Herein, a novel neoHebbian artificial synapse utilizing ReRA... » read more

Hypergraph-based Techniques To Map Spiking Neural Networks on Neuromorphic HW (Politecnico di Milano)
By Technical Paper Link - 25 Jan, 2026 - Comments: 0

A new technical paper titled "A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware" was published by researchers at Politecnico di Milano. Abstract "Executing Spiking Neural Networks (SNNs) on neuromorphic hardware poses the problem of mapping neurons to cores. SNNs operate by propagating spikes between neurons that form a graph through synapses. Neuromorphic hardware mimic... » read more

SpiNNaker2 Neuromorphic Platform: HW-Aware Fine-Tuning of Spiking Q-Networks (TU Dresden Et Al.)
By Technical Paper Link - 05 Aug, 2025 - Comments: 0

A new technical paper titled "Hardware-Aware Fine-Tuning of Spiking Q-Networks on the SpiNNaker2 Neuromorphic Platform" was published by researchers at TU Dresden, ScaDS.AI and Centre for Tactile Internet with Human-in-the-Loop (CeTI). Excerpt "Spiking Neural Networks (SNNs) promise orders-of-magnitude lower power consumption and low-latency inference on neuromorphic hardware for a wide ran... » read more

Hardware Trojan Attack For SNNs (Sorbonne Université, CNRS)
By Technical Paper Link - 03 May, 2025 - Comments: 0

A new technical paper titled "Input-Triggered Hardware Trojan Attack on Spiking Neural Networks" was published by researchers at Sorbonne Universite, CNRS and Queen’s University Belfast. Abstract "Neuromorphic computing based on spiking neural networks (SNNs) is emerging as a promising alternative to traditional artificial neural networks (ANNs), offering unique advantages in terms of low... » read more

Backpropagation Algorithm On Neuromorphic Spiking HW (U. Of Zurich, ETH Zurich, LANL)
By Technical Paper Link - 25 Nov, 2024 - Comments: 0

A new technical paper titled "The backpropagation algorithm implemented on spiking neuromorphic hardware" was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal Institution, London, et al. "This study presents a neuromorphic, spiking backpropagation algorithm based on synfire-gated dynamical information coordination and processing implemented on Intel’s Lo... » read more

Analog Planar Memristor Device: Developing, Designing, and Manufacturing
By Technical Paper Link - 20 Dec, 2023 - Comments: 0

A new technical paper titled "Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks" was published by researchers at Delft University of Technology and Khalifa University. Abstract: "Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation... » read more

A Survey Of Recent Advances In Spiking Neural Networks From Algorithms To HW Acceleration
By Technical Paper Link - 13 Dec, 2023 - Comments: 0

A technical paper titled “Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology” was published by researchers at Intel Labs, University of California Santa Cruz, University of Wisconsin-Madison, and University of Southern California. Abstract: "Neuromorphic computing and, in particular, spiking neural networks (SNNs) have becom... » read more

Neuromorphic Computing: Graphene-Based Memristors For Future AI Hardware From Fabrication To SNNs
By Technical Paper Link - 15 Aug, 2023 - Comments: 0

A technical paper titled “A Review of Graphene-Based Memristive Neuromorphic Devices and Circuits” was published by researchers at James Cook University (Australia) and York University (Canada). Abstract: "As data processing volume increases, the limitations of traditional computers and the need for more efficient computing methods become evident. Neuromorphic computing mimics the brain's... » read more

Spiking Neural Networks: Hardware & Algorithm Developments
By Technical Paper Link - 18 Apr, 2023 - Comments: 0

A new technical paper titled "Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware" was published by researchers at Purdue University, Pennsylvania State University, and Yale University. Excerpt from Abstract: "In this article, we outline several strides that neuromorphic computing based on spiking neural networks (SNNs) has taken over the recent past, a... » read more

MEMprop: Gradient-based Learning To Train Fully Memristive SNNs
By Technical Paper Link - 04 Jul, 2022 - Comments: 0

New technical paper titled "Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays" from IEEE researchers. Abstract "We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs). Our approach harnesses intrinsic device dynamics to trigger naturally arising voltage spikes. These spikes emitted by memristive dynamics are anal... » read more

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