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04/08/2023
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks
The graph colouring problem consists of assigning labels, or colours, to...
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03/26/2023
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning
Offline reinforcement learning agents seek optimal policies from fixed d...
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03/16/2023
Goal-conditioned Offline Reinforcement Learning through State Space Partitioning
Offline reinforcement learning (RL) aims to infer sequential decision po...
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12/08/2022
Model-based trajectory stitching for improved behavioural cloning and its applications
Behavioural cloning (BC) is a commonly used imitation learning method to...
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11/21/2022
Improving TD3-BC: Relaxed Policy Constraint for Offline Learning and Stable Online Fine-Tuning
The ability to discover optimal behaviour from fixed data sets has the p...
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11/21/2022
Model-based Trajectory Stitching for Improved Offline Reinforcement Learning
In many real-world applications, collecting large and high-quality datas...
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07/04/2022
Assessing the Performance of Automated Prediction and Ranking of Patient Age from Chest X-rays Against Clinicians
Understanding the internal physiological changes accompanying the aging ...
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05/20/2022
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation
Combinatorial Optimisation problems arise in several application domains...
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07/27/2021
A persistent homology-based topological loss for CNN-based multi-class segmentation of CMR
Multi-class segmentation of cardiac magnetic resonance (CMR) images seek...
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05/22/2021
Automated Knee X-ray Report Generation
Gathering manually annotated images for the purpose of training a predic...
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09/09/2020
Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning
Training agents to autonomously learn how to use anthropomorphic robotic...
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08/21/2020
A persistent homology-based topological loss function for multi-class CNN segmentation of cardiac MRI
With respect to spatial overlap, CNN-based segmentation of short axis ca...
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08/05/2020
Follow the Object: Curriculum Learning for Manipulation Tasks with Imagined Goals
Learning robot manipulation through deep reinforcement learning in envir...
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06/01/2020
PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals
Learning with sparse rewards remains a significant challenge in reinforc...
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02/17/2020
Adaptive Experience Selection for Policy Gradient
Policy gradient reinforcement learning (RL) algorithms have achieved imp...
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02/12/2020
Connectivity-driven Communication in Multi-agent Reinforcement Learning through Diffusion Processes on Graphs
We discuss the problem of learning collaborative behaviour in multi-agen...
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10/16/2019
Reinforcement Learning for Robotic Manipulation using Simulated Locomotion Demonstrations
Learning robot manipulation policies through reinforcement learning (RL)...
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08/23/2019
Topology-preserving augmentation for CNN-based segmentation of congenital heart defects from 3D paediatric CMR
Patient-specific 3D printing of congenital heart anatomy demands an accu...
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08/14/2019
Skill Transfer in Deep Reinforcement Learning under Morphological Heterogeneity
Transfer learning methods for reinforcement learning (RL) domains facili...
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01/29/2019
Spectral Multi-scale Community Detection in Temporal Networks with an Application
The analysis of temporal networks has a wide area of applications in a w...
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01/12/2019
Improving Coordination in Multi-Agent Deep Reinforcement Learning through Memory-driven Communication
Deep reinforcement learning algorithms have recently been used to train ...
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12/03/2018
Multi-agent Deep Reinforcement Learning with Extremely Noisy Observations
Multi-agent reinforcement learning systems aim to provide interacting ag...
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09/27/2018
A Generative Adversarial Model for Right Ventricle Segmentation
The clinical management of several cardiovascular conditions, such as pu...
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08/31/2018
Automated segmentation on the entire cardiac cycle using a deep learning work-flow
The segmentation of the left ventricle (LV) from CINE MRI images is esse...
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08/06/2018
V-FCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation
Atrial Fibrillation (AF) is a common electro-physiological cardiac disor...
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07/16/2018
Longitudinal detection of radiological abnormalities with time-modulated LSTM
Convolutional neural networks (CNNs) have been successfully employed in ...
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07/11/2018
Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound
The automatic analysis of ultrasound sequences can substantially improve...
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12/11/2017
Deep metric learning for multi-labelled radiographs
Many radiological studies can reveal the presence of several co-existing...
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12/04/2017
Learning to detect chest radiographs containing lung nodules using visual attention networks
Machine learning approaches hold great potential for the automated detec...
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01/29/2017
Random Forest regression for manifold-valued responses
An increasing array of biomedical and computer vision applications requi...
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01/23/2017
Learning what to look in chest X-rays with a recurrent visual attention model
X-rays are commonly performed imaging tests that use small amounts of ra...
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12/08/2016
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
Machine learning analysis of neuroimaging data can accurately predict ch...
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10/28/2016
Adaptive regularization for Lasso models in the context of non-stationary data streams
Large scale, streaming datasets are ubiquitous in modern machine learnin...
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09/28/2016
Recurrent Convolutional Networks for Pulmonary Nodule Detection in CT Imaging
Computed tomography (CT) generates a stack of cross-sectional images cov...
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09/27/2016
Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks
Motivated by the need to automate medical information extraction from fr...
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08/13/2016
Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation
In cardiac magnetic resonance imaging, fully-automatic segmentation of t...
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05/01/2016
Text-mining the NeuroSynth corpus using Deep Boltzmann Machines
Large-scale automated meta-analysis of neuroimaging data has recently es...
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12/07/2015
Learning population and subject-specific brain connectivity networks via Mixed Neighborhood Selection
In neuroimaging data analysis, Gaussian graphical models are often used ...
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11/24/2015
Stopping criteria for boosting automatic experimental design using real-time fMRI with Bayesian optimization
Bayesian optimization has been proposed as a practical and efficient too...
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11/06/2015
Streaming regularization parameter selection via stochastic gradient descent
We propose a framework to perform streaming covariance selection. Our ap...
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07/06/2015
Community detection in multiplex networks using locally adaptive random walks
Multiplex networks, a special type of multilayer networks, are increasin...
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03/04/2015
Sparse multi-view matrix factorisation: a multivariate approach to multiple tissue comparisons
Gene expression levels in a population vary extensively across tissues. ...
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02/09/2015
Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks
Pattern recognition methods using neuroimaging data for the diagnosis of...
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02/09/2015
Deep Neural Networks for Anatomical Brain Segmentation
We present a novel approach to automatically segment magnetic resonance ...
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02/08/2015
Measuring the functional connectome "on-the-fly": towards a new control signal for fMRI-based brain-computer interfaces
There has been an explosion of interest in functional Magnetic Resonance...
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09/24/2013
Random Forests on Distance Matrices for Imaging Genetics Studies
We propose a non-parametric regression methodology, Random Forests on Di...
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03/05/2012
Subspace clustering of high-dimensional data: a predictive approach
In several application domains, high-dimensional observations are collec...
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02/02/2012