Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...
The best kind of follow-up article isn’t one that clarifies a topic that someone got wrong (although I do love that, ...
The Tomorrow’s Quants series explores the skills needed by new quant recruits, drawing on a survey of 39 employers, and six ...
Overview Books provide a deeper understanding of AI concepts beyond running code or tutorials.Hands-on examples and practical ...
New applications of AI and machine learning techniques were presented at Neuroscience 2025, the annual meeting of the Society for Neuroscience and the world’s largest source of emerging news about ...
Frontiers in Neurorobotics has published a new paper by Xiaofei Han and Xin Dou introducing a next-generation artificial intelligence framework that combines graph neural networks and multimodal ...
The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior ...
Abstract: This brief presents an edge-AIoT speech recognition system, which is based on a new spiking feature extraction (SFE) method and a PoolFormer (PF) neural network optimized for implementation ...
The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...
The findings of this study are valuable, offering insights into the neural representation of reversal probability in decision-making tasks, with potential implications for understanding flexible ...
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