This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based ...

Researchers from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences have developed a neural network model based on self-attention mechanisms to rapidly predict radiation ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

St. Petersburg University of Aerospace Instrumentation. For system tasks we could form a rate of messages flows between nodes of different type’s matrix L. The value of element Lij of this matrix is ...

Thus, we propose decoupled dynamic spatial-temporal graph neural network (DDSTGNN), a novel model designed to decouple diffusion and inherent SST signals using data-driven methods. The model ...

Here, we showcase how our graph neural network (GNN)-based implicit solvent (GNNIS) approach can be used to rapidly compute small molecule conformational ensembles in 39 common organic solvents ...

This repository contains an experimental PyTorch implementation exploring the NoProp algorithm, presented in the paper "NOPROP: TRAINING NEURAL NETWORKS WITHOUT BACK-PROPAGATION OR FORWARD-PROPAGATION ...

To efficiently solve the problem, we propose a novel graph neural network (GNN)-based framework. Specifically, we first model the interactions among users and network entities using a heterogeneous ...