Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
As a topic editor (TE), you will take the lead on all editorial decisions for the Research Topic, starting with defining its scope. This allows you to curate research around a topic that interests you ...
Deep learning neural networks, exemplified by models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs), have achieved remarkable ...
Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer ...
Biological neural networks are immensely complex systems underlying all aspects of cognition and behavior. Despite significant advances in neuroscience, a ...
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Small changes make some AI systems more brain-like than others
Artificial intelligence systems that are designed with a biologically inspired architecture can simulate human brain activity ...
A new study finds that artificial intelligence systems that are designed with a biologically inspired architecture can ...
Past psychology and behavioral science studies have identified various ways in which people's acquisition of new knowledge ...
Like other sectors of society, artificial intelligence is fundamentally changing how investors, traders and companies make decisions in financial markets. AI models have the ability to analyze massive ...
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