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Colab Notebooks covering deep learning tools for biomolecular structure prediction and design ...

Recent advancements in technology, particularly in the use of neural networks and electroencephalogram (EEG) signals, have shown promise in improving the accuracy and efficiency of seizure detection.

Abstract: Graph neural networks (GNNs) have been widely used in many fields. Inductive learning has replaced transductive learning as the current mainstream paradigm for GNN training due to its higher ...

These topology-driven DL techniques have notably improved data-driven analysis and mining problems, especially within graph datasets. Recently, graph neural networks (GNNs) have emerged as a popular ...

As the name suggests, neural networks are inspired by the brain. A neural network is designed to mimic how our brains work to recognize complex patterns and improve over time. Neural networks ...

How big of a problem is it worldwide? By The Learning Network A new collection of graphs, maps and charts organized by topic and type from our “What’s Going On in This Graph?” feature.

This work also provides insight into the development of portable single-channel EEG devices with interpretable neural network for driver drowsiness detection. The study is organized as follows.

This region is a common one of interest in dyslexia, yet the researchers measured the I/E balance in only one region of interest, specific to the language network. This study by Glica and colleagues ...