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, aerodynamic noise, machine learning, stochastic algorithms, uncertainties This University of Sheffield PhD project is part of the EPSRC Centre for Doctoral Training in Sustainable Sound Futures programme
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Reinforcement Learning from Human and AI Feedback (S3.5-COM-Peng) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr Bei Peng, Dr Zheng Yuan Application
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in mathematical theory. Unlike standard deep networks, each connection in a KAN learns a continuous function, allowing a richer and more flexible representation of computation. This perspective aligns
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the fact that networks of transistors that form current computers work in very different ways to the massively interconnected networks of synapses and neurons that form truly intelligent systems like
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AI-Driven Facial Movement Analysis for Early Stroke Identification in Pre-Hospital Settings (S3.5-COM-CChen1) School of Computer Science PhD Research Project Competition Funded Students Worldwide Dr
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interconnected computing nodes, actuators and sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity
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of the challenge at once. First, you will create ways for AI models to weave very different kinds of information—images, text, heart-rate graphs, blood glucose—into a single language, so the resulting model can
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. To fill in this gap, in collaboration with industrial partners, the research will develop novel Machine Learning and Computer Vision methods for detecting and localising. These will be used to develop
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Improving Deep Reinforcement Learning through Interactive Human Feedback School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Bei Peng, Dr Robert Loftin Application