:: Library Catalog

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Xehetasun bibliografikoak
Egile Nagusiak:	Soures, Nicholas, Helfer, Peter, Daram, Anurag, Pandit, Tej, Kudithipudi, Dhireesha
Formatua:	Preprint
Argitaratua:	2024
Gaiak:	Neural and Evolutionary Computing Artificial Intelligence Machine Learning
Sarrera elektronikoa:	https://arxiv.org/abs/2409.00021
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Antzeko izenburuak

Genesis: A Spiking Neuromorphic Accelerator With On-chip Continual Learning
nork: Karia, Vedant, et al.
Argitaratua: (2025)

Continuous Spiking Graph Neural Networks
nork: Yin, Nan, et al.
Argitaratua: (2024)

Gradient-Free Continual Learning in Spiking Neural Networks via Inter-Spike Interval Regularization
nork: Roy, Samrendra, et al.
Argitaratua: (2026)

MTSpark: Enabling Multi-Task Learning with Spiking Neural Networks for Generalist Agents
nork: Devkota, Avaneesh, et al.
Argitaratua: (2024)

Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks
nork: Xiao, Mingqing, et al.
Argitaratua: (2024)

STAER: Temporal Aligned Rehearsal for Continual Spiking Neural Network
nork: Gianferrari, Matteo, et al.
Argitaratua: (2026)

Spark: Modular Spiking Neural Networks
nork: Franco, Mario, et al.
Argitaratua: (2026)

Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents
nork: Putra, Rachmad Vidya Wicaksana, et al.
Argitaratua: (2025)

Scalable Learning in Structured Recurrent Spiking Neural Networks without Backpropagation
nork: Tang, Bo, et al.
Argitaratua: (2026)

Enhancing Graph Representation Learning with Attention-Driven Spiking Neural Networks
nork: Yin, Huifeng, et al.
Argitaratua: (2024)

A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
nork: Li, Jintang, et al.
Argitaratua: (2023)

Geometry-Aware Spiking Graph Neural Network
nork: Zhang, Bowen, et al.
Argitaratua: (2025)

Dynamic Spiking Framework for Graph Neural Networks
nork: Yin, Nan, et al.
Argitaratua: (2023)

Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks
nork: Dequino, Alberto, et al.
Argitaratua: (2024)

The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning
nork: Nguyen, Manh V., et al.
Argitaratua: (2024)

Adversarially Robust Spiking Neural Networks Through Conversion
nork: Özdenizci, Ozan, et al.
Argitaratua: (2023)

TESS: A Scalable Temporally and Spatially Local Learning Rule for Spiking Neural Networks
nork: Apolinario, Marco Paul E., et al.
Argitaratua: (2025)

The Enduring Dominance of Deep Neural Networks: A Critical Analysis of the Fundamental Limitations of Quantum Machine Learning and Spiking Neural Networks
nork: Ishikawa, Takehiro
Argitaratua: (2025)

Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning
nork: Xiao, Mingqing, et al.
Argitaratua: (2024)

Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm
nork: Ghader, Mohammadnavid, et al.
Argitaratua: (2025)

Understanding the Functional Roles of Modelling Components in Spiking Neural Networks
nork: Yin, Huifeng, et al.
Argitaratua: (2024)

SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network-based Embedded AI Systems
nork: Putra, Rachmad Vidya Wicaksana, et al.
Argitaratua: (2024)

SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning
nork: Chen, Dong, et al.
Argitaratua: (2024)

SPEAR: Structured Pruning for Spiking Neural Networks via Synaptic Operation Estimation and Reinforcement Learning
nork: Xie, Hui, et al.
Argitaratua: (2025)

Average-Over-Time Spiking Neural Networks for Uncertainty Estimation in Regression
nork: Sun, Tao, et al.
Argitaratua: (2024)

A Scalable Hybrid Training Approach for Recurrent Spiking Neural Networks
nork: Baronig, Maximilian, et al.
Argitaratua: (2025)

Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks
nork: Xiao, Mingqing, et al.
Argitaratua: (2024)

Globally Optimal Training of Spiking Neural Networks via Parameter Reconstruction
nork: Udupi, Himanshu, et al.
Argitaratua: (2026)

Training Spiking Neural Networks via Augmented Direct Feedback Alignment
nork: Zhang, Yongbo, et al.
Argitaratua: (2024)

Direct Training Needs Regularisation: Anytime Optimal Inference Spiking Neural Network
nork: Wu, Dengyu, et al.
Argitaratua: (2024)

Toward End-to-End Bearing Fault Diagnosis for Industrial Scenarios with Spiking Neural Networks
nork: Zuo, Lin, et al.
Argitaratua: (2024)

Benchmarking Fairness in Spiking Neural Networks: Data Bias, Spurious Features, and Hardware Effects
nork: He, Hudi, et al.
Argitaratua: (2026)

Gradient-Free Training of Spiking Neural Networks via Low-Rank Evolution Strategies
nork: Patankar, Dhruv, et al.
Argitaratua: (2026)

A frugal Spiking Neural Network for unsupervised classification of continuous multivariate temporal data
nork: Pokala, Sai Deepesh, et al.
Argitaratua: (2024)

Izhikevich-Inspired Temporal Dynamics for Enhancing Privacy, Efficiency, and Transferability in Spiking Neural Networks
nork: Moshruba, Ayana, et al.
Argitaratua: (2025)

SGNNBench: A Holistic Evaluation of Spiking Graph Neural Network on Large-scale Graph
nork: Zhang, Huizhe, et al.
Argitaratua: (2025)

Knowing When to Stop: Delay-Adaptive Spiking Neural Network Classifiers with Reliability Guarantees
nork: Chen, Jiechen, et al.
Argitaratua: (2023)

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients
nork: Zhou, Feifan, et al.
Argitaratua: (2026)

Fully Spiking Actor Network with Intra-layer Connections for Reinforcement Learning
nork: Chen, Ding, et al.
Argitaratua: (2024)

Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunities
nork: Wang, Huan, et al.
Argitaratua: (2023)