AIMC Topic: Neural Networks, Computer

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Multi-agent self-attention reinforcement learning for multi-USV hunting target.

Neural networks : the official journal of the International Neural Network Society
A reinforcement learning (RL) method based on the multi-head self-attention (MSA) mechanism is proposed to solve the challenge of multiple unmanned surface vehicles (multi-USV) hunting target at the surface. The kinematic, dynamic, and environmental ...

A systematic review of artificial intelligence techniques based on electroencephalography analysis in the diagnosis of epilepsy disorders: A clinical perspective.

Epilepsy research
In recent years, Artificial Intelligence (AI), with a specific emphasis on attention mechanisms instead of conventional Deep Learning (DL) or Machine Learning (ML), has demonstrated significant applicability across diverse medical domains. This paper...

Abnormalities of brain dynamics based on large-scale cortical network modeling in autism spectrum disorder.

Neural networks : the official journal of the International Neural Network Society
Synaptic increase is a common phenomenon in the brain of autism spectrum disorder (ASD). However, the impact of increased synapses on the neurophysiological activity of ASD remains unclear. To address this, we propose a large-scale cortical network m...

The butterfly effect in neural networks: Unveiling hyperbolic chaos through parameter sensitivity.

Neural networks : the official journal of the International Neural Network Society
Neural networks often excel in short-horizon tasks, but their long-term reliability is less assured. We demonstrate that even a minimal architecture, trained on near-periodic data, can exhibit hyperbolic chaotic behavior after a small parameter pertu...

Progressive fine-to-coarse reconstruction for accurate low-bit post-training quantization in vision transformers.

Neural networks : the official journal of the International Neural Network Society
Due to its efficiency, Post-Training Quantization (PTQ) has been widely adopted for compressing Vision Transformers (ViTs). However, when quantized into low-bit representations, there is often a significant performance drop compared to their full-pre...

Escarcitys: A framework for enhancing medical image classification performance in scarcity of trainable samples scenarios.

Neural networks : the official journal of the International Neural Network Society
In the field of healthcare, the acquisition and annotation of medical images present significant challenges, resulting in a scarcity of trainable samples. This data limitation hinders the performance of deep learning models, creating bottlenecks in c...

3DBench: A scalable benchmark for object and scene-level instruction-tuning of 3D large language models.

Neural networks : the official journal of the International Neural Network Society
Recent assessments of Multi-Modal Large Language Models (MLLMs) have been thorough. However, a detailed benchmark that integrates point cloud data with language for MLLMs remains absent, leading to superficial comparisons that obscure advancements in...

Multiple-input and multiple-output encoders with DNA-based winner-take-all neural Networks.

Neural networks : the official journal of the International Neural Network Society
DNA logic circuits are essential building blocks for molecular computers. Traditional molecular logic circuits primarily use basic gate circuits as computational units, achieving complex functions via multiple cascades. However, even simple logical f...

Knowledge graph information bottleneck enhanced molecular representation learning.

Neural networks : the official journal of the International Neural Network Society
Effective molecular representation learning (MRL) is essential for advancing molecular property prediction. In recent years, graph-based MRL methods have made significant progress by effectively utilizing the topology structure of molecules. Research...