Yike Guo

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Imperial College London

Professor of Computing Science and Director at Data Science Institute, Imperial College London

Digital twins based on bidirectional LSTM and GAN for modelling COVID-19

The outbreak of the coronavirus disease 2019 (COVID-19) has now spread t...
02/03/2021 ∙ by Cesar Quilodran Casas, et al. ∙ 0 ∙ share

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OmiEmbed: reconstruct comprehensive phenotypic information from multi-omics data using multi-task deep learning

High-dimensional omics data contains intrinsic biomedical information th...
02/03/2021 ∙ by Xiaoyu Zhang, et al. ∙ 13 ∙ share

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A Blockchain-based Trust System for Decentralised Applications: When trustless needs trust

Blockchain technology has been envisaged to commence an era of decentral...
01/26/2021 ∙ by Nguyen Truong, et al. ∙ 0 ∙ share

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BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecede...
01/24/2021 ∙ by Zhe Peng, et al. ∙ 0 ∙ share

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Adversarially trained LSTMs on reduced order models of urban air pollution simulations

This paper presents an approach to improve computational fluid dynamics ...
01/05/2021 ∙ by Cesar Quilodran Casas, et al. ∙ 0 ∙ share

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Revealing the Transmission Dynamics of COVID-19: A Bayesian Framework for R_t Estimation

In epidemiological modelling, the instantaneous reproduction number, R_t...
12/22/2020 ∙ by Xian Yang, et al. ∙ 0 ∙ share

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Privacy Preservation in Federated Learning: Insights from the GDPR Perspective

Along with the blooming of AI and Machine Learning-based applications an...
11/10/2020 ∙ by Nguyen Truong, et al. ∙ 0 ∙ share

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Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling

Machine learning has been widely adopted for medical image analysis in r...
06/26/2020 ∙ by Chengliang Dai, et al. ∙ 0 ∙ share

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An Epidemiological Modelling Approach for Covid19 via Data Assimilation

The global pandemic of the 2019-nCov requires the evaluation of policy i...
04/25/2020 ∙ by Philip Nadler, et al. ∙ 20 ∙ share

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Regularizing Deep Multi-Task Networks using Orthogonal Gradients

Deep neural networks are a promising approach towards multi-task learnin...
12/14/2019 ∙ by Mihai Suteu, et al. ∙ 0 ∙ share

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Biologically inspired architectures for sample-efficient deep reinforcement learning

Deep reinforcement learning requires a heavy price in terms of sample ef...
11/25/2019 ∙ by Pierre H. Richemond, et al. ∙ 0 ∙ share

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Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction

Gliomas are the most common malignant brain tumourswith intrinsic hetero...
11/19/2019 ∙ by Shuo Wang, et al. ∙ 0 ∙ share

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Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records

The extraction of phenotype information which is naturally contained in ...
11/10/2019 ∙ by Jingqing Zhang, et al. ∙ 0 ∙ share

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Transfer Learning from Partial Annotations for Whole Brain Segmentation

Brain MR image segmentation is a key task in neuroimaging studies. It is...
08/28/2019 ∙ by Chengliang Dai, et al. ∙ 0 ∙ share

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Blockchain-based Personal Data Management: From Fiction to Solution

The emerging blockchain technology has enabled various decentralised app...
08/28/2019 ∙ by Nguyen Truong, et al. ∙ 0 ∙ share

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Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification

Different aspects of a clinical sample can be revealed by multiple types...
08/17/2019 ∙ by Xiaoyu Zhang, et al. ∙ 0 ∙ share

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Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

In the recent years, convolutional neural networks have transformed the ...
07/05/2019 ∙ by Wenjia Bai, et al. ∙ 6 ∙ share

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A backdoor attack against LSTM-based text classification systems

With the widespread use of deep learning system in many applications, th...
05/29/2019 ∙ by Jiazhu Dai, et al. ∙ 0 ∙ share

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Static Activation Function Normalization

Recent seminal work at the intersection of deep neural networks practice...
05/03/2019 ∙ by Pierre H. Richemond, et al. ∙ 0 ∙ share

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GDPR-Compliant Personal Data Management: A Blockchain-based Solution

The General Data Protection Regulation (GDPR) gives control of personal ...
04/05/2019 ∙ by Nguyen Binh Truong, et al. ∙ 0 ∙ share

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Integrating Semantic Knowledge to Tackle Zero-shot Text Classification

Insufficient or even unavailable training data of emerging classes is a ...
03/29/2019 ∙ by Jingqing Zhang, et al. ∙ 0 ∙ share

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Combining learning rate decay and weight decay with complexity gradient descent - Part I

The role of L^2 regularization, in the specific case of deep neural netw...
02/07/2019 ∙ by Pierre H. Richemond, et al. ∙ 0 ∙ share

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Deep Sequence Learning with Auxiliary Information for Traffic Prediction

Predicting traffic conditions from online route queries is a challenging...
06/13/2018 ∙ by Binbing Liao, et al. ∙ 0 ∙ share

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Generative Creativity: Adversarial Learning for Bionic Design

Bionic design refers to an approach of generative creativity in which a ...
05/19/2018 ∙ by Simiao Yu, et al. ∙ 0 ∙ share

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The Future of Spreadsheets in the Big Data Era

The humble spreadsheet is the most widely used data storage, manipulatio...
01/30/2018 ∙ by David Birch, et al. ∙ 0 ∙ share

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Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security

Deep learning methods can play a crucial role in anomaly detection, pred...
11/20/2017 ∙ by Hao Dong, et al. ∙ 0 ∙ share

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TensorLayer: A Versatile Library for Efficient Deep Learning Development

Deep learning has enabled major advances in the fields of computer visio...
07/26/2017 ∙ by Hao Dong, et al. ∙ 0 ∙ share

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Semantic Image Synthesis via Adversarial Learning

In this paper, we propose a way of synthesizing realistic images directl...
07/21/2017 ∙ by Hao Dong, et al. ∙ 0 ∙ share

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Deep De-Aliasing for Fast Compressive Sensing MRI

Fast Magnetic Resonance Imaging (MRI) is highly in demand for many clini...
05/19/2017 ∙ by Simiao Yu, et al. ∙ 0 ∙ share

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Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks

A major challenge in brain tumor treatment planning and quantitative eva...
05/10/2017 ∙ by Hao Dong, et al. ∙ 0 ∙ share

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Deep Poincare Map For Robust Medical Image Segmentation

Precise segmentation is a prerequisite for an accurate quantification of...
03/27/2017 ∙ by Yuanhan Mo, et al. ∙ 0 ∙ share

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I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation

Translating information between text and image is a fundamental problem ...
03/20/2017 ∙ by Hao Dong, et al. ∙ 0 ∙ share

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DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

The present study proposes a deep learning model, named DeepSleepNet, fo...
03/12/2017 ∙ by Akara Supratak, et al. ∙ 0 ∙ share

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Unsupervised Image-to-Image Translation with Generative Adversarial Networks

It's useful to automatically transform an image from its original form t...
01/10/2017 ∙ by Hao Dong, et al. ∙ 0 ∙ share

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Mixed Neural Network Approach for Temporal Sleep Stage Classification

This paper proposes a practical approach to addressing limitations posed...
10/15/2016 ∙ by Hao Dong, et al. ∙ 0 ∙ share

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Automatic Sleep Stage Scoring with Single-Channel EEG Using Convolutional Neural Networks

We used convolutional neural networks (CNNs) for automatic sleep stage s...
10/05/2016 ∙ by Orestis Tsinalis, et al. ∙ 0 ∙ share

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DropNeuron: Simplifying the Structure of Deep Neural Networks

Deep learning using multi-layer neural networks (NNs) architecture manif...
06/23/2016 ∙ by Wei Pan, et al. ∙ 0 ∙ share

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Yike Guo

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