Neural ordinary differential equations (neural ODEs) are a relatively recent development (. https://arxiv.org/abs/1806.07366). in the field of machine learning, where the hidden state dynamics of certain neural network architectures can be reformulated as numerical solutions of a differential equation. Read more
How does the human brain work? As you read this text, the pixels on your screen are converted into a series of spike trains passing along the neural pathways in your brain, allowing you to understand the content. Read more
Spiking Neural Networks (SNNs) represent the so called ‘third generation’ of artificial neural network models, that bridge the gap between neuroscience and artificial intelligence by relying on biologically realistic models of neurons and network architectures to carry out computations. Read more
Neural ranking models for information retrieval (IR) use deep neural networks to rank search results in response to a query. Recently proposed neural models learn representations of language from raw text that can bridge the gap between query and document vocabulary. Read more
This project is part of a unique cohort based 4-year fully funded PhD programme at the. UKRI Centre for Doctoral Training in Safe and Trusted AI. Read more
During the past two decades, blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) has become the scientific technique of choice for investigating human brain function in the field of cognitive neuroscience. Read more
One core measure of cognitive control is that of response inhibition. Appropriately enacting response inhibition is a trait that may be lessened as… Read more
The current state of the art in generative modelling is dominated by neural networks. Despite their impressive performance on many benchmark tasks, these algorithms do not provide tractable inference for common and important queries, e.g. Read more
Supervisors. Principal supervisor. Dr. Yue Li (XJTLU). Co-supervisor. Professor Weihua Pei (JITRI). Co-supervisor. Professor Hai-Ning Liang (XJTLU). Read more
As part of the model-based approaches to safe and trusted AI, this project aims to shed light on the phenomenon of robust generalisation as a trade-off in geometric deep networks. . Read more
Mammals give birth to dependent offspring and significant parental involvement is required to ensure offspring survive. During pregnancy and in the early postpartum period, hormones act on neural circuitry to bring about key changes in a mother's mood and behaviour. Read more
Feedback control enables dynamical systems to interact autonomously and safely with the real-world. The classical approach to feedback control system design involves first identifying a model of the system and then solving an optimal control problem to generate a control policy. Read more
Speech is a complex task requiring highly coordinated movements of a large group of respiratory, laryngeal and articulatory muscles and involves precise integration with auditory and somatosensory feedback to plan and execute speech movements. Read more
The project will continue research started at the University of Reading on animats - robotic platforms controlled in real time by activity of biological neuron cultures - and will investigate the methods for implementing efficient conditioning protocols. Read more
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