:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Chen, Hongrui, Liu, Xingchen, Kara, Levent Burak
Format:	Preprint
Published:	2024
Subjects:	Neural and Evolutionary Computing Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2404.08708
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Machine Unlearning using Forgetting Neural Networks
by: Hatua, Amartya, et al.
Published: (2024)

Multi-Task Optimization over Networks of Tasks
by: Hatzky, Julian, et al.
Published: (2026)

Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization
by: Tao, Peng, et al.
Published: (2024)

Closing the gap: Optimizing Guidance and Control Networks through Neural ODEs
by: Origer, Sebastien, et al.
Published: (2024)

Quantum-Evolutionary Neural Networks for Multi-Agent Federated Learning
by: Lala, Aarav, et al.
Published: (2025)

Neural Architecture Search using Particle Swarm and Ant Colony Optimization
by: Lankford, Séamus, et al.
Published: (2024)

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

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

Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks
by: Mazandarani, Mehran, et al.
Published: (2025)

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

Recurrent Neural Networks Learn to Store and Generate Sequences using Non-Linear Representations
by: Csordás, Róbert, et al.
Published: (2024)

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver
by: Zhou, Changliang, et al.
Published: (2024)

Restricted Bayesian Neural Network
by: Ganguly, Sourav, et al.
Published: (2024)

Deep Oscillatory Neural Network
by: Rohan, Nurani Rajagopal, et al.
Published: (2024)

Time Elastic Neural Networks
by: Marteau, Pierre-François
Published: (2024)

Polysemanticity and Capacity in Neural Networks
by: Scherlis, Adam, et al.
Published: (2022)

Offline Multi-Objective Optimization
by: Xue, Ke, et al.
Published: (2024)

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

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

Continuous Spiking Graph Neural Networks
by: Yin, Nan, et al.
Published: (2024)

Sheaf Neural Networks and biomedical applications
by: Mehrab, Aneeqa, et al.
Published: (2026)

Spark: Modular Spiking Neural Networks
by: Franco, Mario, et al.
Published: (2026)

Large-scale Multi-objective Feature Selection: A Multi-phase Search Space Shrinking Approach
by: Bidgoli, Azam Asilian, et al.
Published: (2024)

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

Sensitivity-Aware Mixed-Precision Quantization and Width Optimization of Deep Neural Networks Through Cluster-Based Tree-Structured Parzen Estimation
by: Azizi, Seyedarmin, et al.
Published: (2023)

Half-Space Feature Learning in Neural Networks
by: Yadav, Mahesh Lorik, et al.
Published: (2024)

Mechanistic Neural Networks for Scientific Machine Learning
by: Pervez, Adeel, et al.
Published: (2024)

Structure of Artificial Neural Networks -- Empirical Investigations
by: Stier, Julian
Published: (2024)

Invariant Representations with Stochastically Quantized Neural Networks
by: Cerrato, Mattia, et al.
Published: (2022)

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

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

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

LLS: Local Learning Rule for Deep Neural Networks Inspired by Neural Activity Synchronization
by: Apolinario, Marco Paul E., et al.
Published: (2024)

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

Learning from Emergence: A Study on Proactively Inhibiting the Monosemantic Neurons of Artificial Neural Networks
by: Wang, Jiachuan, et al.
Published: (2023)

PropNEAT -- Efficient GPU-Compatible Backpropagation over NeuroEvolutionary Augmenting Topology Networks
by: Merry, Michael, et al.
Published: (2024)

Meta-Learning Loss Functions for Deep Neural Networks
by: Raymond, Christian
Published: (2024)

DL101 Neural Network Outputs and Loss Functions
by: Berzal, Fernando
Published: (2025)

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