spiking neural networks - Robuta Search

https://www.ornl.gov/publication/abisko-deep-codesign-architecture-spiking-neural-networks-using-novel-neuromorphic Abisko: Deep codesign of an architecture for spiking neural networks using novel neuromorphic... The Abisko project aims to develop an energy-efficient spiking neural network (SNN) computing architecture and software system capable of autonomous learning... spiking neural networks https://ir.cwi.nl/pub/20937 Centrum Wiskunde & Informatica: New model for spiking neural networks : Hoe?Zo! Radio, NTR,... spiking neural networks https://arxiv.org/abs/2509.23253v1 [2509.23253v1] Training Deep Normalization-Free Spiking Neural Networks with Lateral Inhibition Abstract page for arXiv paper 2509.23253v1: Training Deep Normalization-Free Spiking Neural Networks with Lateral Inhibition spiking neural networks https://scholars.cityu.edu.hk/en/publications/an-online-unsupervised-structural-plasticity-algorithm-for-spikin/ An online unsupervised structural plasticity algorithm for spiking neural networks - CityUHK... spiking neural networks online unsupervised structural plasticity https://publikationen.bibliothek.kit.edu/1000139776 Motion representation with spiking neural networks for graspin... Die Natur bedient sich Millionen von Jahren der Evolution, um adaptive physikalische Systeme mit effizienten Steuerungsstrategien zu erzeugen. Im Gegensatz zur spiking neural networks motion representation https://impact.ornl.gov/en/publications/snnvis-visualizing-graph-embedding-of-evolutionary-optimization-f/ SNNVis: Visualizing Graph Embedding of Evolutionary Optimization for Spiking Neural Networks - Oak... spiking neural networks https://ieeetv.ieee.org/ondemand/ieee-icassp-2020-virtual-conference-may-2020/6376/training-deep-spiking-neural-networks-for-energyefficient-neuromorphic-computing Training Deep Spiking Neural Networks For Energy-Efficient Neuromorphic Computing | IEEETV Spiking Neural Networks (SNNs) encode input information temporally using sparse spiking events, which can be harnessed to achieve higher computational... spiking neural networks for energy neuromorphic computing training deep https://impact.ornl.gov/en/publications/resilience-and-robustness-of-spiking-neural-networks-for-neuromor/ Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems - Oak Ridge National... spiking neural networks https://arxiv.org/abs/2504.14015 [2504.14015] Causal pieces: analysing and improving spiking neural networks piece by piece Abstract page for arXiv paper 2504.14015: Causal pieces: analysing and improving spiking neural networks piece by piece spiking neural networks https://ub01.uni-tuebingen.de/xmlui/handle/10900/125915 Signal Denoising with Recurrent Spiking Neural Networks and Active Tuning spiking neural networks signal denoising recurrent active https://arxiv.org/html/2509.21345v2 Neuromorphic Deployment of Spiking Neural Networks for Cognitive Load Classification in Air Traffic... spiking neural networks https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2020.00662/full Frontiers | Optimizing the Energy Consumption of Spiking Neural Networks for Neuromorphic... In the last few years, spiking neural networks have been demonstrated to perform on par with regular convolutional neural networks. Several works have propos... spiking neural networks energy consumption frontiers optimizing https://portal.fis.tum.de/en/publications/mathematical-foundations-of-spiking-neural-networks-strengths-cha/ Mathematical Foundations of Spiking Neural Networks: Strengths, challenges, and computational... spiking neural networks mathematical foundations strengths challenges computational https://uwspace.uwaterloo.ca/items/be024076-5a82-47c9-8348-65b240a24138 Collective Dynamics of Large-Scale Spiking Neural Networks by Mean-Field Theory The brain contains a large number of neurons, each of which typically has thousands of synaptic connections. Its functionality, whether function or... spiking neural networks large scale https://www.surrey.ac.uk/research-projects/general-purpose-learning-algorithms-spiking-neural-networks General-purpose learning algorithms for spiking neural networks | University of Surrey The project will deliver a series of learning algorithms for artificial networks of spiking neurons that are general-purpose (that is, not tied to a specific... spiking neural networks general purpose learning algorithms university of https://portal.fis.tum.de/de/publications/mathematical-foundations-of-spiking-neural-networks-strengths-cha/ Mathematical Foundations of Spiking Neural Networks: Strengths, challenges, and computational... spiking neural networks mathematical foundations strengths challenges computational https://www.ideals.illinois.edu/items/50594 Analysis framework for adaptive spiking neural networks | IDEALS spiking neural networks analysis framework adaptive ideals https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2024.1412559/full Frontiers | Composing recurrent spiking neural networks using locally-recurrent motifs and... In neural circuits, recurrent connectivity plays a crucial role in network function and stability.However, existing recurrent spiking neural networks (RSNNs)... spiking neural networks frontiers composing recurrent using https://portal.fis.tum.de/en/publications/capturing-uncertainty-over-time-for-spiking-neural-networks-by-ex/ Capturing Uncertainty over Time for Spiking Neural Networks by Exploiting Conformal Prediction Sets... spiking neural networks https://arxiv.org/abs/2010.01729v5 [2010.01729v5] Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks... Abstract page for arXiv paper 2010.01729v5: Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch https://research.ibm.com/publications/conversion-of-artificial-recurrent-neural-networks-to-spiking-neural-networks-for-low-power-neuromorphic-hardware Conversion of artificial recurrent neural networks to spiking neural networks for low-power... Conversion of artificial recurrent neural networks to spiking neural networks for low-power neuromorphic hardware for ICRC 2016 by Peter U. Diehl et al. recurrent neural networks conversion artificial https://infoscience.epfl.ch/entities/publication/a85e7acb-cee7-4d6c-9672-a5c1720a4eb1 A Time Encoding Approach to Training Spiking Neural Networks While Spiking Neural Networks (SNNs) have been gaining in popularity, it seems that the algorithms used to train them are not powerful enough to solve the same... a time encoding approach training spiking https://research.vu.nl/en/publications/leveraging-spiking-deep-neural-networks-to-understand-the-neural-/ Leveraging Spiking Deep Neural Networks to Understand the Neural Mechanisms Underlying Selective... deep neural networks to understand leveraging spiking https://arxiv.org/abs/2209.03501 [2209.03501] Macroscopic Dynamics of Neural Networks with Heterogeneous Spiking Thresholds Abstract page for arXiv paper 2209.03501: Macroscopic Dynamics of Neural Networks with Heterogeneous Spiking Thresholds neural networks macroscopic dynamics https://journals.gmu.edu/jssr/article/view/3484 Using Spiking Neural Networks for Control Applications at the Edge | Journal of Student-Scientists'... https://par.nsf.gov/biblio/10403834-solving-quadratic-unconstrained-binary-optimization-collaborative-spiking-neural-networks Solving Quadratic Unconstrained Binary Optimization with Collaborative Spiking Neural Networks |... This page contains metadata information for the record with PAR ID 10403834 solving quadratic binary optimization collaborative https://uwspace.uwaterloo.ca/items/62d63319-e415-4652-8457-9cbaba7dd32f Driving Scene Understanding using Spiking Neural Networks One of the applications of AI lies in developing intelligent systems for safe on-road driving, other than building and perfecting self-driving vehicles, and... scene understanding driving using spiking neural