The University of Sheffield

∙ Sheffield , United Kingdom ∙ 0 followers

A world top-100 university and number one in the UK for student satisfaction in the 2014-15 Times Higher Student Experience Survey.

Featured Researchers

Wei Liu
216 publications
Wei Li
128 publications
Peng Wang
97 publications
Jie Zhang
74 publications
Isabelle Augenstein
50 publications
Ke Sun
46 publications
Neil D. Lawrence
36 publications
Lucia Specia
33 publications
James Hensman
30 publications
Mauricio A. Álvarez
30 publications
Kalina Bontcheva
29 publications

Physically-inspired Gaussian processes for transcriptional regulation in Drosophila melanogaster

The regulatory process in Drosophila melanogaster is thoroughly studied ...
08/29/2018 ∙ by Andrés F. López-Lopera, et al. ∙ 12 ∙ share

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Differentially Private Regression and Classification with Sparse Gaussian Processes

A continuing challenge for machine learning is providing methods to perf...
09/19/2019 ∙ by Michael Thomas Smith, et al. ∙ 12 ∙ share

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A Foliated View of Transfer Learning

Transfer learning considers a learning process where a new task is solve...
08/02/2020 ∙ by Janith Petangoda, et al. ∙ 12 ∙ share

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Non-linear process convolutions for multi-output Gaussian processes

The paper introduces a non-linear version of the process convolution for...
10/10/2018 ∙ by Mauricio A. Álvarez, et al. ∙ 10 ∙ share

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Machine Learning for a Low-cost Air Pollution Network

Data collection in economically constrained countries often necessitates...
11/28/2019 ∙ by Michael T. Smith, et al. ∙ 9 ∙ share

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Classification Aware Neural Topic Model and its Application on a New COVID-19 Disinformation Corpus

The explosion of disinformation related to the COVID-19 pandemic has ove...
06/05/2020 ∙ by Xingyi Song, et al. ∙ 8 ∙ share

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Adversarial Vulnerability Bounds for Gaussian Process Classification

Machine learning (ML) classification is increasingly used in safety-crit...
09/19/2019 ∙ by Michael Thomas Smith, et al. ∙ 6 ∙ share

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Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes

This paper introduces a method for inference of heterogeneous dynamical ...
06/21/2019 ∙ by Wil O. C. Ward, et al. ∙ 5 ∙ share

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Automatic Assessment of Full Left Ventricular Coverage in Cardiac Cine Magnetic Resonance Imaging with Fisher-Discriminative 3D CNN

Cardiac magnetic resonance (CMR) images play a growing role in the diagn...
11/06/2018 ∙ by Le Zhang, et al. ∙ 4 ∙ share

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Gaussian Process Manifold Interpolation for Probabilistic Atrial Activation Maps and Uncertain Conduction Velocity

In patients with atrial fibrillation, local activation time (LAT) maps a...
04/22/2020 ∙ by Sam Coveney, et al. ∙ 4 ∙ share

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Tri-graph Information Propagation for Polypharmacy Side Effect Prediction

The use of drug combinations often leads to polypharmacy side effects (P...
01/28/2020 ∙ by Hao Xu, et al. ∙ 1 ∙ share

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Antenna Array Signal Processing for Quaternion-Valued Wireless Communication Systems

Quaternion-valued wireless communication systems have been studied in th...
04/11/2015 ∙ by Wei Liu, et al. ∙ 0 ∙ share

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Channel Equalization and Beamforming for Quaternion-Valued Wireless Communication Systems

Quaternion-valued wireless communication systems have been studied in th...
05/31/2015 ∙ by Wei Liu, et al. ∙ 0 ∙ share

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Compressive Sensing Based Design of Sparse Tripole Arrays

This paper considers the problem of designing sparse linear tripole arra...
03/29/2016 ∙ by Matthew Hawes, et al. ∙ 0 ∙ share

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Location and Orientation Optimisation for Spatially Stretched Tripole Arrays Based on Compressive Sensing

The design of sparse spatially stretched tripole arrays is an important ...
02/01/2017 ∙ by Matthew Hawes, et al. ∙ 0 ∙ share

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A Compressive Sensing Based Approach to Sparse Wideband Array Design

Sparse wideband sensor array design for sensor location optimisation is ...
03/19/2014 ∙ by Matthew B. Hawes, et al. ∙ 0 ∙ share

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Automatic Genre and Show Identification of Broadcast Media

Huge amounts of digital videos are being produced and broadcast every da...
06/10/2016 ∙ by Mortaza Doulaty, et al. ∙ 0 ∙ share

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How Wrong Am I? - Studying Adversarial Examples and their Impact on Uncertainty in Gaussian Process Machine Learning Models

Machine learning models are vulnerable to adversarial examples: minor, i...
11/17/2017 ∙ by Kathrin Grosse, et al. ∙ 0 ∙ share

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GANGs: Generative Adversarial Network Games

Generative Adversarial Networks (GAN) have become one of the most succes...
12/02/2017 ∙ by Frans A. Oliehoek, et al. ∙ 0 ∙ share

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A generalised framework for detailed classification of swimming paths inside the Morris Water Maze

The Morris Water Maze is commonly used in behavioural neuroscience for t...
11/20/2017 ∙ by Avgoustinos Vouros, et al. ∙ 0 ∙ share

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Is Epicurus the father of Reinforcement Learning?

The Epicurean Philosophy is commonly thought as simplistic and hedonisti...
10/12/2017 ∙ by Eleni Vasilaki, et al. ∙ 0 ∙ share

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Gold Standard Online Debates Summaries and First Experiments Towards Automatic Summarization of Online Debate Data

Usage of online textual media is steadily increasing. Daily, more and mo...
08/15/2017 ∙ by Nattapong Sanchan, et al. ∙ 0 ∙ share

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Automatic Summarization of Online Debates

Debate summarization is one of the novel and challenging research areas ...
08/15/2017 ∙ by Nattapong Sanchan, et al. ∙ 0 ∙ share

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Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description

We present the results from the second shared task on multimodal machine...
10/19/2017 ∙ by Desmond Elliott, et al. ∙ 0 ∙ share

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Stance Detection with Bidirectional Conditional Encoding

Stance detection is the task of classifying the attitude expressed in a ...
06/17/2016 ∙ by Isabelle Augenstein, et al. ∙ 0 ∙ share

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Turing learning: a metric-free approach to inferring behavior and its application to swarms

We propose Turing Learning, a novel system identification method for inf...
03/15/2016 ∙ by Wei Li, et al. ∙ 0 ∙ share

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SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours

Media is full of false claims. Even Oxford Dictionaries named "post-trut...
04/20/2017 ∙ by Leon Derczynski, et al. ∙ 0 ∙ share

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Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes

Often in machine learning, data are collected as a combination of multip...
05/27/2017 ∙ by Zhenwen Dai, et al. ∙ 0 ∙ share

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Compressive Sensing Approaches for Autonomous Object Detection in Video Sequences

Video analytics requires operating with large amounts of data. Compressi...
04/27/2017 ∙ by Danil Kuzin, et al. ∙ 0 ∙ share

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Structured Sparse Modelling with Hierarchical GP

In this paper a new Bayesian model for sparse linear regression with a s...
04/27/2017 ∙ by Danil Kuzin, et al. ∙ 0 ∙ share

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PCT and Beyond: Towards a Computational Framework for `Intelligent' Communicative Systems

Recent years have witnessed increasing interest in the potential benefit...
11/16/2016 ∙ by Prof. Roger K. Moore, et al. ∙ 0 ∙ share

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A stochastically verifiable autonomous control architecture with reasoning

A new agent architecture called Limited Instruction Set Agent (LISA) is ...
11/10/2016 ∙ by Paolo Izzo, et al. ∙ 0 ∙ share

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General Upper Bounds on the Running Time of Parallel Evolutionary Algorithms

We present a new method for analyzing the running time of parallel evolu...
06/15/2012 ∙ by Jörg Lässig, et al. ∙ 0 ∙ share

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Is spoken language all-or-nothing? Implications for future speech-based human-machine interaction

Recent years have seen significant market penetration for voice-based pe...
07/18/2016 ∙ by Roger K. Moore, et al. ∙ 0 ∙ share

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Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding

Magnetic Resonance Imaging (MRI) offers high-resolution in vivo imaging ...
05/07/2017 ∙ by Yawen Huang, et al. ∙ 0 ∙ share

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Learning Methods for Dynamic Topic Modeling in Automated Behaviour Analysis

Semi-supervised and unsupervised systems provide operators with invaluab...
11/02/2016 ∙ by Olga Isupova, et al. ∙ 0 ∙ share

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Unsupervised Learning with Imbalanced Data via Structure Consolidation Latent Variable Model

Unsupervised learning on imbalanced data is challenging because, when gi...
06/30/2016 ∙ by Fariba Yousefi, et al. ∙ 0 ∙ share

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Dynamic Hierarchical Dirichlet Process for Abnormal Behaviour Detection in Video

This paper proposes a novel dynamic Hierarchical Dirichlet Process topic...
06/27/2016 ∙ by Olga Isupova, et al. ∙ 0 ∙ share

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Differentially Private Gaussian Processes

A major challenge for machine learning is increasing the availability of...
06/02/2016 ∙ by Michael Thomas Smith, et al. ∙ 0 ∙ share

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Variational Inference for Uncertainty on the Inputs of Gaussian Process Models

The Gaussian process latent variable model (GP-LVM) provides a flexible ...
09/08/2014 ∙ by Andreas C. Damianou, et al. ∙ 0 ∙ share

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Recurrent Gaussian Processes

We define Recurrent Gaussian Processes (RGP) models, a general family of...
11/20/2015 ∙ by César Lincoln C. Mattos, et al. ∙ 0 ∙ share

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Variational Auto-encoded Deep Gaussian Processes

We develop a scalable deep non-parametric generative model by augmenting...
11/19/2015 ∙ by Zhenwen Dai, et al. ∙ 0 ∙ share

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GLASSES: Relieving The Myopia Of Bayesian Optimisation

We present GLASSES: Global optimisation with Look-Ahead through Stochast...
10/21/2015 ∙ by Javier Gonzalez, et al. ∙ 0 ∙ share

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A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation

In this paper, we look to address the problem of estimating the dynamic ...
09/21/2015 ∙ by Matthew Hawes, et al. ∙ 0 ∙ share

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MCMC for Variationally Sparse Gaussian Processes

Gaussian process (GP) models form a core part of probabilistic machine l...
06/12/2015 ∙ by James Hensman, et al. ∙ 0 ∙ share

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Spike and Slab Gaussian Process Latent Variable Models

The Gaussian process latent variable model (GP-LVM) is a popular approac...
05/10/2015 ∙ by Zhenwen Dai, et al. ∙ 0 ∙ share

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Bayesian Optimization for Synthetic Gene Design

We address the problem of synthetic gene design using Bayesian optimizat...
05/07/2015 ∙ by Javier Gonzalez, et al. ∙ 0 ∙ share

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Gaussian Process Pseudo-Likelihood Models for Sequence Labeling

Several machine learning problems arising in natural language processing...
12/25/2014 ∙ by P. K. Srijith, et al. ∙ 0 ∙ share

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Generalized Canonical Correlation Analysis and Its Application to Blind Source Separation Based on a Dual-Linear Predictor Structure

Blind source separation (BSS) is one of the most important and establish...
03/09/2014 ∙ by Wei Liu, et al. ∙ 0 ∙ share

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A Version of Geiringer-like Theorem for Decision Making in the Environments with Randomness and Incomplete Information

Purpose: In recent years Monte-Carlo sampling methods, such as Monte Car...
10/20/2011 ∙ by Boris Mitavskiy, et al. ∙ 0 ∙ share

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