AIMC Topic: Neural Networks, Computer

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Generalization limits of Graph Neural Networks in identity effects learning.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have emerged as a powerful tool for data-driven learning on various graph domains. They are usually based on a message-passing mechanism and have gained increasing popularity for their intuitive formulation, which is clos...

GSSCL: A framework for Graph Self-Supervised Curriculum Learning based on clustering label smoothing.

Neural networks : the official journal of the International Neural Network Society
Graph self-supervised learning is an effective technique for learning common knowledge from unlabeled graph data through pretext tasks. To capture the interrelationships between nodes and their essential roles globally, existing methods use clusterin...

Drug-target prediction through self supervised learning with dual task ensemble approach.

Computational biology and chemistry
Drug-Target interaction (DTI) prediction, a transformative approach in pharmaceutical research, seeks novel therapeutic applications for computational method based virtual screening, existing drugs to address untreated diseases and discovery of exist...

Smart monitoring solution for dengue infection control: A digital twin-inspired approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In the realm of smart healthcare, precise monitoring and prediction services are crucial for mitigating the impact of infectious diseases. This study introduces an innovative digital twin technology-inspired monitoring archi...

Rapid estimation of left ventricular contractility with a physics-informed neural network inverse modeling approach.

Artificial intelligence in medicine
Physics-based computer models based on numerical solutions of the governing equations generally cannot make rapid predictions, which in turn limits their applications in the clinic. To address this issue, we developed a physics-informed neural networ...

From Noise to Knowledge: Diffusion Probabilistic Model-Based Neural Inference of Gene Regulatory Networks.

Journal of computational biology : a journal of computational molecular cell biology
Understanding gene regulatory networks (GRNs) is crucial for elucidating cellular mechanisms and advancing therapeutic interventions. Original methods for GRN inference from bulk expression data often struggled with the high dimensionality and inhere...

Quantitative investigation and intelligent forecasting of thermal conductivity in lime-modified red clay.

PloS one
This paper delves into the engineering applications of lime-stabilized red clay, a highly water-sensitive material, particularly in the context of the climatic conditions prevalent in the Dalian region. We systematically investigate the impact of wat...

InstructNet: A novel approach for multi-label instruction classification through advanced deep learning.

PloS one
People use search engines for various topics and items, from daily essentials to more aspirational and specialized objects. Therefore, search engines have taken over as people's preferred resource. The "How To" prefix has become familiar and widely u...

Plant lncRNA-miRNA Interaction Prediction Based on Counterfactual Heterogeneous Graph Attention Network.

Interdisciplinary sciences, computational life sciences
Identifying interactions between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) provides a new perspective for understanding regulatory relationships in plant life processes. Recently, computational methods based on graph neural networks (GNNs...

A deep drug prediction framework for viral infectious diseases using an optimizer-based ensemble of convolutional neural network: COVID-19 as a case study.

Molecular diversity
The SARS-CoV-2 outbreak highlights the persistent vulnerability of humanity to epidemics and emerging microbial threats, emphasizing the lack of time to develop disease-specific treatments. Therefore, it appears beneficial to utilize existing resourc...