Researchers at The Hong Kong University of Science and Technology (HKUST) School of Engineering have developed a novel reinforcement learning–based generative model to predict neural signals, creating ...

History may soon repeat itself with a novel new platform: networks of AI agents carrying out instructions from prompts and sharing them with other AI agents, which could spread the instructions ...

In the remote and rain-lashed Scottish highlands, UK utility SSE has a job trying to maintain the tens of thousands of wooden poles that carry electricity across its far-flung network.

Abstract: Recently, recurrent neural network (RNN) models have been extensively investigated for addressing time-dependent nonlinear optimization problems. However, few existing RNN models take ...

RNN stands for recurrent neural network. It is one of the classic architectures for modeling sequences. RNN is simple, but learning it can help us understand the foundations, such as encoding, loss ...

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In this important study, the authors model reinforcement-learning experiments using a recurrent neural network. The work examines if the detailed credit assignment necessary for back-propagation ...

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 ...

ABSTRACT: SQL injection attacks pose a critical threat to web application security, exploiting vulnerabilities to gain access, or modify sensitive data. Traditional rule-based and machine learning ...