Yike Guo

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Imperial College London

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

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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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Yike Guo

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