Cover Image

Accuracy-Efficiency Trade-Offs in Spiking Neural Networks: A Lempel-Ziv Complexity Perspective on Learning Rules

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rudnicka, Zofia, Szczepanski, Janusz, Pregowska, Agnieszka
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning Neurons and Cognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Impact of Neuron Models on Spiking Neural Networks performance. A Complexity Based Classification Approach
by: Rudnicka, Zofia, et al.
Published: (2025)

Learning Internal Biological Neuron Parameters and Complexity-Based Encoding for Improved Spiking Neural Networks Performance
by: Rudnicka, Zofia, et al.
Published: (2025)

Improving Liver Disease Diagnosis with SNNDeep: A Custom Spiking Neural Network Using Diverse Learning Algorithms
by: Rudnicka, Zofia, et al.
Published: (2025)

Artificial Intelligence-based algorithms in medical image scan seg-mentation and intelligent visual-content generation -- a concise overview
by: Rudnicka, Zofia, et al.
Published: (2024)

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection
by: Rudnicka, Zofia, et al.
Published: (2025)

Health Digital Twins Supported by Artificial Intelligence-based Algorithms and Extended Reality in Cardiology
by: Rudnicka, Zofia, et al.
Published: (2024)

Implicit neural representations for larval zebrafish brain microscopy: a reproducible benchmark on the MapZebrain atlas
by: Pregowska, Agnieszka
Published: (2026)

Hybrid Spiking Neural Networks for Low-Power Intra-Cortical Brain-Machine Interfaces
by: Vasilache, Alexandru, et al.
Published: (2024)

Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization
by: Ouyang, Kaichen
Published: (2025)

Modular Boundaries in Recurrent Neural Networks
by: Tanner, Jacob, et al.
Published: (2023)

Cross-Modal Representational Knowledge Distillation for Enhanced Spike-Informed LFP Modeling
by: Erturk, Eray, et al.
Published: (2025)

Functional Classification of Spiking Signal Data Using Artificial Intelligence Techniques: A Review
by: Sharifrazi, Danial, et al.
Published: (2024)

Brain Networks and Intelligence: A Graph Neural Network Based Approach to Resting State fMRI Data
by: Thapaliya, Bishal, et al.
Published: (2023)

Contrastive Self-Supervised Learning As Neural Manifold Packing
by: Zhang, Guanming, et al.
Published: (2025)

Critical Learning Periods Emerge Even in Deep Linear Networks
by: Kleinman, Michael, et al.
Published: (2023)

ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks
by: Sun, Kai, et al.
Published: (2025)

Cortex-Inspired Continual Learning: Unsupervised Instantiation and Recovery of Functional Task Networks
by: McKee, Kevin, et al.
Published: (2026)

Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification
by: Noman, Fuad, et al.
Published: (2021)

DSAM: A Deep Learning Framework for Analyzing Temporal and Spatial Dynamics in Brain Networks
by: Thapaliya, Bishal, et al.
Published: (2024)

Neural Encoding and Decoding at Scale
by: Zhang, Yizi, et al.
Published: (2025)

Neuro-Symbolic Decoding of Neural Activity
by: Wang, Yanchen, et al.
Published: (2026)

Complex behavior from intrinsic motivation to occupy action-state path space
by: Ramírez-Ruiz, Jorge, et al.
Published: (2022)

JEDI: Jointly Embedded Inference of Neural Dynamics
by: Jamkhandi, Anirudh, et al.
Published: (2026)

Allostatic Control of Persistent States in Spiking Neural Networks for perception and computation
by: Htet, Aung, et al.
Published: (2025)

Credit Assignment via Neural Manifold Noise Correlation
by: Kang, Byungwoo, et al.
Published: (2026)

BRAID: Input-Driven Nonlinear Dynamical Modeling of Neural-Behavioral Data
by: Vahidi, Parsa, et al.
Published: (2025)

Discovering Mechanistic Models of Neural Activity: System Identification in an in Silico Zebrafish
by: Lueckmann, Jan-Matthis, et al.
Published: (2026)

Modelling the Effects of Hearing Loss on Neural Coding in the Auditory Midbrain with Variational Conditioning
by: Pellatt, Lloyd, et al.
Published: (2025)

Clustering Inductive Biases with Unrolled Networks
by: Huml, Jonathan, et al.
Published: (2023)

A Spiking Neural Network based on Neural Manifold for Augmenting Intracortical Brain-Computer Interface Data
by: Zheng, Shengjie, et al.
Published: (2022)

BaRISTA: Brain Scale Informed Spatiotemporal Representation of Human Intracranial Neural Activity
by: Oganesian, Lucine L., et al.
Published: (2025)

NOBLE -- Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models
by: Ghafourpour, Luca, et al.
Published: (2025)

Contrastive Graph Pooling for Explainable Classification of Brain Networks
by: Xu, Jiaxing, et al.
Published: (2023)

Learning Human-Aligned Representations with Contrastive Learning and Generative Similarity
by: Marjieh, Raja, et al.
Published: (2024)

Learning to Abstract Visuomotor Mappings using Meta-Reinforcement Learning
by: Velazquez-Vargas, Carlos A., et al.
Published: (2024)

How scanning probe microscopy can be supported by Artificial Intelligence and quantum computing
by: Pregowska, Agnieszka, et al.
Published: (2024)

Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification
by: Xu, Jiaxing, et al.
Published: (2024)

Emergent Language Symbolic Autoencoder (ELSA) with Weak Supervision to Model Hierarchical Brain Networks
by: Latheef, Ammar Ahmed Pallikonda, et al.
Published: (2024)

Deep Learning without Weight Symmetry
by: Ji-An, Li, et al.
Published: (2024)

Bayes or Heisenberg: Who(se) Rules?
by: Tresp, Volker, et al.
Published: (2025)