In this work, we propose a strategy to map deep graph learning architectures for knowledge graph reasoning to neuromorphic architectures. Based on the insight that randomly initialized and untrained ...

Figure 2.Building blocks of geometric deep learning according to the study by Sivakumar (2023). Graph Convolutional Networks (GCNs) are a particular type of neural network that may be used to ...

In this article, we present a novel approach to predicting chemical structures from their infrared (IR) spectra using deep Q-learning. IR spectra measurements are widely used in chemical analysis ...

The application of deep learning algorithms in protein structure prediction has greatly influenced drug discovery and development. Accurate protein structures are crucial for understanding biological ...

4. Technology application and future direction: Deep learning improves protein structure prediction and provides new possibilities for drug design, antibody development, and synthetic biology. "We ...