Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...
The Kennedy College of Science, Richard A. Miner School of Computer & Information Sciences, invites you to attend a doctoral dissertation proposal defense by Nidhi Vakil, titled: "Foundations for ...
Abstract: Dynamic graph representation learning aims to generate low-dimensional latent vector representations of graphs or nodes at various time points from evolving graph datas, which are then used ...
Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...
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