
Unifying Homophily and Heterophily Network Transformation via Motifs
Higherorder proximity (HOP) is fundamental for most network embedding m...
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Physicallyinspired Gaussian processes for transcriptional regulation in Drosophila melanogaster
The regulatory process in Drosophila melanogaster is thoroughly studied ...
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Differentially Private Regression and Classification with Sparse Gaussian Processes
A continuing challenge for machine learning is providing methods to perf...
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A Foliated View of Transfer Learning
Transfer learning considers a learning process where a new task is solve...
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Nonlinear process convolutions for multioutput Gaussian processes
The paper introduces a nonlinear version of the process convolution for...
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Machine Learning for a Lowcost Air Pollution Network
Data collection in economically constrained countries often necessitates...
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Classification Aware Neural Topic Model and its Application on a New COVID19 Disinformation Corpus
The explosion of disinformation related to the COVID19 pandemic has ove...
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Adversarial Vulnerability Bounds for Gaussian Process Classification
Machine learning (ML) classification is increasingly used in safetycrit...
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Variational Bridge Constructs for Grey Box Modelling with Gaussian Processes
This paper introduces a method for inference of heterogeneous dynamical ...
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Automatic Assessment of Full Left Ventricular Coverage in Cardiac Cine Magnetic Resonance Imaging with FisherDiscriminative 3D CNN
Cardiac magnetic resonance (CMR) images play a growing role in the diagn...
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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...
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Trigraph Information Propagation for Polypharmacy Side Effect Prediction
The use of drug combinations often leads to polypharmacy side effects (P...
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Antenna Array Signal Processing for QuaternionValued Wireless Communication Systems
Quaternionvalued wireless communication systems have been studied in th...
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Channel Equalization and Beamforming for QuaternionValued Wireless Communication Systems
Quaternionvalued wireless communication systems have been studied in th...
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Compressive Sensing Based Design of Sparse Tripole Arrays
This paper considers the problem of designing sparse linear tripole arra...
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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 ...
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A Compressive Sensing Based Approach to Sparse Wideband Array Design
Sparse wideband sensor array design for sensor location optimisation is ...
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Automatic Genre and Show Identification of Broadcast Media
Huge amounts of digital videos are being produced and broadcast every da...
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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...
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GANGs: Generative Adversarial Network Games
Generative Adversarial Networks (GAN) have become one of the most succes...
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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...
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Is Epicurus the father of Reinforcement Learning?
The Epicurean Philosophy is commonly thought as simplistic and hedonisti...
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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...
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Automatic Summarization of Online Debates
Debate summarization is one of the novel and challenging research areas ...
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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...
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Stance Detection with Bidirectional Conditional Encoding
Stance detection is the task of classifying the attitude expressed in a ...
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Turing learning: a metricfree approach to inferring behavior and its application to swarms
We propose Turing Learning, a novel system identification method for inf...
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SemEval2017 Task 8: RumourEval: Determining rumour veracity and support for rumours
Media is full of false claims. Even Oxford Dictionaries named "posttrut...
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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...
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Compressive Sensing Approaches for Autonomous Object Detection in Video Sequences
Video analytics requires operating with large amounts of data. Compressi...
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Structured Sparse Modelling with Hierarchical GP
In this paper a new Bayesian model for sparse linear regression with a s...
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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...
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A stochastically verifiable autonomous control architecture with reasoning
A new agent architecture called Limited Instruction Set Agent (LISA) is ...
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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...
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Is spoken language allornothing? Implications for future speechbased humanmachine interaction
Recent years have seen significant market penetration for voicebased pe...
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Simultaneous SuperResolution and CrossModality Synthesis of 3D Medical Images using WeaklySupervised Joint Convolutional Sparse Coding
Magnetic Resonance Imaging (MRI) offers highresolution in vivo imaging ...
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Learning Methods for Dynamic Topic Modeling in Automated Behaviour Analysis
Semisupervised and unsupervised systems provide operators with invaluab...
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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...
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Dynamic Hierarchical Dirichlet Process for Abnormal Behaviour Detection in Video
This paper proposes a novel dynamic Hierarchical Dirichlet Process topic...
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Differentially Private Gaussian Processes
A major challenge for machine learning is increasing the availability of...
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Variational Inference for Uncertainty on the Inputs of Gaussian Process Models
The Gaussian process latent variable model (GPLVM) provides a flexible ...
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Recurrent Gaussian Processes
We define Recurrent Gaussian Processes (RGP) models, a general family of...
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Variational Autoencoded Deep Gaussian Processes
We develop a scalable deep nonparametric generative model by augmenting...
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GLASSES: Relieving The Myopia Of Bayesian Optimisation
We present GLASSES: Global optimisation with LookAhead through Stochast...
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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 ...
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MCMC for Variationally Sparse Gaussian Processes
Gaussian process (GP) models form a core part of probabilistic machine l...
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Spike and Slab Gaussian Process Latent Variable Models
The Gaussian process latent variable model (GPLVM) is a popular approac...
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Bayesian Optimization for Synthetic Gene Design
We address the problem of synthetic gene design using Bayesian optimizat...
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Gaussian Process PseudoLikelihood Models for Sequence Labeling
Several machine learning problems arising in natural language processing...
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Generalized Canonical Correlation Analysis and Its Application to Blind Source Separation Based on a DualLinear Predictor Structure
Blind source separation (BSS) is one of the most important and establish...
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