b'Yike Guo'

research

∙ 07/15/2022

ChoreoGraph: Music-conditioned Automatic Dance Choreography over a Style and Tempo Consistent Dynamic Graph

To generate dance that temporally and aesthetically matches the music is...

Ho Yin Au, et al. ∙

research

∙ 07/15/2022

A Dual-Masked Auto-Encoder for Robust Motion Capture with Spatial-Temporal Skeletal Token Completion

Multi-person motion capture can be challenging due to ambiguities caused...

Junkun Jiang, et al. ∙

research

∙ 06/02/2022

Suggestive Annotation of Brain MR Images with Gradient-guided Sampling

Machine learning has been widely adopted for medical image analysis in r...

Chengliang Dai, et al. ∙

research

∙ 05/24/2022

Medical Scientific Table-to-Text Generation with Human-in-the-Loop under the Data Sparsity Constraint

Structured (tabular) data in the preclinical and clinical domains contai...

Heng-Yi Wu, et al. ∙

research

∙ 05/18/2022

A Scalable Workflow to Build Machine Learning Classifiers with Clinician-in-the-Loop to Identify Patients in Specific Diseases

Clinicians may rely on medical coding systems such as International Clas...

Jingqing Zhang, et al. ∙

research

∙ 04/19/2022

Unsupervised Numerical Reasoning to Extract Phenotypes from Clinical Text by Leveraging External Knowledge

Extracting phenotypes from clinical text has been shown to be useful for...

Ashwani Tanwar, et al. ∙

research

∙ 04/13/2022

Receding Neuron Importances for Structured Pruning

Structured pruning efficiently compresses networks by identifying and re...

Mihai Suteu, et al. ∙

research

∙ 01/18/2022

Label-dependent and event-guided interpretable disease risk prediction using EHRs

Electronic health records (EHRs) contain patients' heterogeneous data th...

Shuai Niu, et al. ∙

research

∙ 01/18/2022

Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health Records

Disease risk prediction has attracted increasing attention in the field ...

Shuai Niu, et al. ∙

research

∙ 11/27/2021

OmiTrans: generative adversarial networks based omics-to-omics translation framework

With the rapid development of high-throughput experimental technologies,...

Xiaoyu Zhang, et al. ∙

research

∙ 09/04/2021

Self-Supervised Detection of Contextual Synonyms in a Multi-Class Setting: Phenotype Annotation Use Case

Contextualised word embeddings is a powerful tool to detect contextual s...

Jingqing Zhang, et al. ∙

research

∙ 07/24/2021

Clinical Utility of the Automatic Phenotype Annotation in Unstructured Clinical Notes: ICU Use Cases

Clinical notes contain information not present elsewhere, including drug...

Jingqing Zhang, et al. ∙

research

∙ 05/26/2021

XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data

Deep learning based approaches have proven promising to model omics data...

Eloise Withnell, et al. ∙

research

∙ 04/13/2021

Adversarial autoencoders and adversarial LSTM for improved forecasts of urban air pollution simulations

This paper presents an approach to improve the forecast of computational...

Cesar Quilodran Casas, et al. ∙

research

∙ 03/31/2021

MOAI: A methodology for evaluating the impact of indoor airflow in the transmission of COVID-19

Epidemiology models play a key role in understanding and responding to t...

Axel Oehmichen, et al. ∙

research

∙ 03/29/2021

Product semantics translation from brain activity via adversarial learning

A small change of design semantics may affect a user's satisfaction with...

Pan Wang, et al. ∙

research

∙ 02/03/2021

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...

Cesar Quilodran Casas, et al. ∙

research

∙ 02/03/2021

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

High-dimensional omics data contains intrinsic biomedical information th...

Xiaoyu Zhang, et al. ∙

research

∙ 01/26/2021

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

Blockchain technology has been envisaged to commence an era of decentral...

Nguyen Truong, et al. ∙

research

∙ 01/24/2021

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

The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecede...

Zhe Peng, et al. ∙

research

∙ 01/05/2021

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

This paper presents an approach to improve computational fluid dynamics ...

Cesar Quilodran Casas, et al. ∙

research

∙ 12/22/2020

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

In epidemiological modelling, the instantaneous reproduction number, R_t...

Xian Yang, et al. ∙

research

∙ 11/10/2020

Privacy Preservation in Federated Learning: Insights from the GDPR Perspective

Along with the blooming of AI and Machine Learning-based applications an...

Nguyen Truong, et al. ∙

research

∙ 06/26/2020

Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling

Machine learning has been widely adopted for medical image analysis in r...

Chengliang Dai, et al. ∙

research

∙ 04/25/2020

An Epidemiological Modelling Approach for Covid19 via Data Assimilation

The global pandemic of the 2019-nCov requires the evaluation of policy i...

Philip Nadler, et al. ∙

research

∙ 12/14/2019

Regularizing Deep Multi-Task Networks using Orthogonal Gradients

Deep neural networks are a promising approach towards multi-task learnin...

Mihai Suteu, et al. ∙

research

∙ 11/25/2019

Biologically inspired architectures for sample-efficient deep reinforcement learning

Deep reinforcement learning requires a heavy price in terms of sample ef...

Pierre H. Richemond, et al. ∙

research

∙ 11/19/2019

Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction

Gliomas are the most common malignant brain tumourswith intrinsic hetero...

Shuo Wang, et al. ∙

research

∙ 11/10/2019

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

The extraction of phenotype information which is naturally contained in ...

Jingqing Zhang, et al. ∙

research

∙ 08/28/2019

Transfer Learning from Partial Annotations for Whole Brain Segmentation

Brain MR image segmentation is a key task in neuroimaging studies. It is...

Chengliang Dai, et al. ∙

research

∙ 08/28/2019

Blockchain-based Personal Data Management: From Fiction to Solution

The emerging blockchain technology has enabled various decentralised app...

Nguyen Truong, et al. ∙

research

∙ 08/17/2019

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

Different aspects of a clinical sample can be revealed by multiple types...

Xiaoyu Zhang, et al. ∙

research

∙ 07/05/2019

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

In the recent years, convolutional neural networks have transformed the ...

Wenjia Bai, et al. ∙

research

∙ 05/29/2019

A backdoor attack against LSTM-based text classification systems

With the widespread use of deep learning system in many applications, th...

Jiazhu Dai, et al. ∙

research

∙ 05/03/2019

Static Activation Function Normalization

Recent seminal work at the intersection of deep neural networks practice...

Pierre H. Richemond, et al. ∙

research

∙ 04/05/2019

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

The General Data Protection Regulation (GDPR) gives control of personal ...

Nguyen Binh Truong, et al. ∙

research

∙ 03/29/2019

Integrating Semantic Knowledge to Tackle Zero-shot Text Classification

Insufficient or even unavailable training data of emerging classes is a ...

Jingqing Zhang, et al. ∙

research

∙ 02/07/2019

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...

Pierre H. Richemond, et al. ∙

research

∙ 06/13/2018

Deep Sequence Learning with Auxiliary Information for Traffic Prediction

Predicting traffic conditions from online route queries is a challenging...

Binbing Liao, et al. ∙

research

∙ 05/19/2018

Generative Creativity: Adversarial Learning for Bionic Design

Bionic design refers to an approach of generative creativity in which a ...

Simiao Yu, et al. ∙

research

∙ 01/30/2018

The Future of Spreadsheets in the Big Data Era

The humble spreadsheet is the most widely used data storage, manipulatio...

David Birch, et al. ∙

research

∙ 11/20/2017

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...

Hao Dong, et al. ∙

research

∙ 07/26/2017

TensorLayer: A Versatile Library for Efficient Deep Learning Development

Deep learning has enabled major advances in the fields of computer visio...

Hao Dong, et al. ∙

research

∙ 07/21/2017

Semantic Image Synthesis via Adversarial Learning

In this paper, we propose a way of synthesizing realistic images directl...

Hao Dong, et al. ∙

research

∙ 05/19/2017

Deep De-Aliasing for Fast Compressive Sensing MRI

Fast Magnetic Resonance Imaging (MRI) is highly in demand for many clini...

Simiao Yu, et al. ∙

research

∙ 05/10/2017

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

A major challenge in brain tumor treatment planning and quantitative eva...

Hao Dong, et al. ∙

research

∙ 03/27/2017

Deep Poincare Map For Robust Medical Image Segmentation

Precise segmentation is a prerequisite for an accurate quantification of...

Yuanhan Mo, et al. ∙

research

∙ 03/20/2017

I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation

Translating information between text and image is a fundamental problem ...

Hao Dong, et al. ∙

research

∙ 03/12/2017

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...

Akara Supratak, et al. ∙

research

∙ 01/10/2017

Unsupervised Image-to-Image Translation with Generative Adversarial Networks

It's useful to automatically transform an image from its original form t...

Hao Dong, et al. ∙

Yike Guo

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