AIMC Topic: Algorithms

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QTypeMix: Enhancing multi-agent cooperative strategies through heterogeneous and homogeneous value decomposition.

Neural networks : the official journal of the International Neural Network Society
In multi-agent cooperative tasks, the presence of heterogeneous agents is familiar. Compared to cooperation among homogeneous agents, collaboration requires considering the best-suited sub-tasks for each agent. However, the operation of multi-agent s...

A Robust and Efficient Representation-based DNA Storage Architecture by Deep Learning.

Small methods
As one main form of multimedia data, images play a critical role in various applications. In this paper, a representation-based architecture is proposed which takes advantage of the outstanding representation and image-generation abilities of deep le...

H control for fractional order neural networks with uncertainties subject to deception attacks via Improved memory-event-triggered scheme and Its application.

Neural networks : the official journal of the International Neural Network Society
The article discusses an improved memory-event-triggered strategy for H control class of fractional-order neural networks (FONNs) with uncertainties, which are vulnerable to deception attacks. The system under consideration is simultaneously influenc...

Motif-aware curriculum learning for node classification.

Neural networks : the official journal of the International Neural Network Society
Node classification, seeking to predict the categories of unlabeled nodes, is a crucial task in graph learning. One of the most popular methods for node classification is currently Graph Neural Networks (GNNs). However, conventional GNNs assign equal...

Simplified PCNet with robustness.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have garnered significant attention for their success in learning the representation of homophilic or heterophilic graphs. However, they cannot generalize well to real-world graphs with different levels of homophily. In r...

Modeling document causal structure with a hypergraph for event causality identification.

Neural networks : the official journal of the International Neural Network Society
Document-level event causality identification (ECI) aims to detect causal relations in between event mentions in a document. Some recent approaches model diverse connections in between events, such as syntactic dependency and etc., with a graph neura...

Two-dimensional identification of lower limb gait features based on the variational modal decomposition of sEMG signal and convolutional neural network.

Gait & posture
BACKGROUND: Gait feature recognition is crucial to improve the efficiency and coordination of exoskeleton assistance. The recognition methods based on surface electromyographic (sEMG) signals are popular. However, the recognition accuracy of these me...

Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation.

Computer methods and programs in biomedicine
BACKGROUND: Data sharing in healthcare is vital for advancing research and personalized medicine. However, the process is hindered by privacy, ethical, and legal challenges associated with patient data. Synthetic data generation emerges as a promisin...

A hybrid artificial neural network and multi-objective genetic algorithm approach to optimize extraction conditions of Mentha longifolia and biological activities.

Scientific reports
In this work, artificial neural network coupled with multi-objective genetic algorithm (ANN-NSGA-II) has been used to develop a model and optimize the conditions for the extracting of the Mentha longifolia (L.) L. plant. Input parameters were extract...

EEG-based emotion recognition using multi-scale dynamic CNN and gated transformer.

Scientific reports
Emotions play a crucial role in human thoughts, cognitive processes, and decision-making. EEG has become a widely utilized tool in emotion recognition due to its high temporal resolution, real-time monitoring capabilities, portability, and cost-effec...