The importance of graphs in physics lab experiments. Learn how visual data reveals patterns, relationships, and experimental errors, making results clearer and more meaningful. #PhysicsLab ...

Abstract: Dynamic Graph Neural Networks (GNNs) combine temporal information with GNNs to capture structural, temporal, and contextual relationships in dynamic graphs simultaneously, leading to ...

A comprehensive deep learning model for molecular toxicity prediction using a multimodal approach. The model combines molecular graphs, SMILES sequences, 2D structure images, and NMR spectra to ...

Abstract: Camera calibration plays an important role in machine vision systems as it directly impacts the measurement accuracy. However, traditional calibration methods usually perform poorly when ...

Materials science is an interdisciplinary field concerned with the understanding and application of the properties of matter. Materials scientists study the connections between the underlying ...

Background: Bladder cancer (BCA) shows significant prognostic differences between non-muscle-invasive (NMIBC) and muscle-invasive (MIBC) forms. While NMIBC frequently recurs and can progress to ...