
Classification of COVID19 via Homology of CTSCAN
In this worldwide spread of SARSCoV2 (COVID19) infection, it is of ut...
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Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning
Training agents to autonomously learn how to use anthropomorphic robotic...
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Unifying machine learning and quantum chemistry  a deep neural network for molecular wavefunctions
Machine learning advances chemistry and materials science by enabling la...
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A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services
Rough sleeping is a chronic problem faced by some of the most disadvanta...
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Probabilistic solution of chaotic dynamical system inverse problems using Bayesian Artificial Neural Networks
This paper demonstrates the application of Bayesian Artificial Neural Ne...
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PlanGAN: Modelbased Planning With Sparse Rewards and Multiple Goals
Learning with sparse rewards remains a significant challenge in reinforc...
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VFCNN: Volumetric Fully Convolution Neural Network For Automatic Atrial Segmentation
Atrial Fibrillation (AF) is a common electrophysiological cardiac disor...
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Adaptive Learning Rate Clipping Stabilizes Learning
Artificial neural network training with stochastic gradient descent can ...
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Improving Coordination in MultiAgent Deep Reinforcement Learning through Memorydriven Communication
Deep reinforcement learning algorithms have recently been used to train ...
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Model inference for Ordinary Differential Equations by parametric polynomial kernel regression
Model inference for dynamical systems aims to estimate the future behavi...
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Deep Learningbased Vehicle Behaviour Prediction For Autonomous Driving Applications: A Review
Behaviour prediction function of an autonomous vehicle predicts the futu...
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Multiple Object Forecasting: Predicting Future Object Locations in Diverse Environments
This paper introduces the problem of multiple object forecasting (MOF), ...
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Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods
The increasing availability of data presents an opportunity to calibrate...
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PanNuke Dataset Extension, Insights and Baselines
The emerging area of computational pathology (CPath) is ripe ground for ...
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A deep neural network for molecular wave functions in quasiatomic minimal basis representation
The emergence of machine learning methods in quantum chemistry provides ...
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Multiagent Deep Reinforcement Learning with Extremely Noisy Observations
Multiagent reinforcement learning systems aim to provide interacting ag...
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VISIR: Visual and Semantic Image Label Refinement
The social media explosion has populated the Internet with a wealth of i...
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Scalable Partial Explainability in Neural Networks via Flexible Activation Functions
Achieving transparency in blackbox deep learning algorithms is still an...
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Follow the Object: Curriculum Learning for Manipulation Tasks with Imagined Goals
Learning robot manipulation through deep reinforcement learning in envir...
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ZeroCost Proxies Meet Differentiable Architecture Search
Differentiable neural architecture search (NAS) has attracted significan...
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Improving Electron Micrograph SignaltoNoise with an Atrous Convolutional EncoderDecoder
We present an atrous convolutional encoderdecoder trained to denoise 51...
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Autoencoders, Kernels, and Multilayer Perceptrons for Electron Micrograph Restoration and Compression
We present 14 autoencoders, 15 kernels and 14 multilayer perceptrons for...
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Warwick Image Forensics Dataset for Device Fingerprinting In Multimedia Forensics
Device fingerprints like sensor pattern noise (SPN) are widely used for ...
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AgeOriented Face Synthesis with Conditional Discriminator Pool and Adversarial Triplet Loss
The vanilla Generative Adversarial Networks (GAN) are commonly used to g...
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Local2Global: Scaling global representation learning on graphs via local training
We propose a decentralised "local2global" approach to graph representati...
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On the Constrained Leastcost Tour Problem
We introduce the Constrained Leastcost Tour (CLT) problem: given an und...
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ContextAware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images
Digital histology images are amenable to the application of convolutiona...
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Towards Deep Learning Models for Psychological State Prediction using Smartphone Data: Challenges and Opportunities
There is an increasing interest in exploiting mobile sensing technologie...
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Mental Sampling in Multimodal Representations
Both resources in the natural environment and concepts in a semantic spa...
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Learning Graphical Models from a Distributed Stream
A current challenge for data management systems is to support the constr...
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3D Object Reconstruction from a Single Depth View with Adversarial Learning
In this paper, we propose a novel 3DRecGAN approach, which reconstructs...
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Programming Patterns in Dataflow Matrix Machines and Generalized Recurrent Neural Nets
Dataflow matrix machines arise naturally in the context of synchronous d...
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Dataflow matrix machines as programmable, dynamically expandable, selfreferential generalized recurrent neural networks
Dataflow matrix machines are a powerful generalization of recurrent neur...
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Dataflow Matrix Machines as a Generalization of Recurrent Neural Networks
Dataflow matrix machines are a powerful generalization of recurrent neur...
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Linear Models of Computation and Program Learning
We consider two classes of computations which admit taking linear combin...
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Turing at SemEval2017 Task 8: Sequential Approach to Rumour Stance Classification with BranchLSTM
This paper describes team Turing's submission to SemEval 2017 RumourEval...
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Confusing Deep Convolution Networks by Relabelling
Deep convolutional neural networks have become the gold standard for ima...
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Efficient batchwise dropout training using submatrices
Dropout is a popular technique for regularizing artificial neural networ...
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Geometry and Dynamics for Markov Chain Monte Carlo
Markov Chain Monte Carlo methods have revolutionised mathematical comput...
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Sparse arrays of signatures for online character recognition
In mathematics the signature of a path is a collection of iterated integ...
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Monotonicity of Fitness Landscapes and Mutation Rate Control
The typical view in evolutionary biology is that mutation rates are mini...
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Directed expected utility networks
A variety of statistical graphical models have been defined to represent...
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A Reduction for Optimizing Lattice Submodular Functions with Diminishing Returns
A function f: Z_+^E →R_+ is DRsubmodular if it satisfies f( + χ_i) f (...
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Random Coordinate Descent Methods for Minimizing Decomposable Submodular Functions
Submodular function minimization is a fundamental optimization problem t...
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Accelerating a hybrid continuumatomistic fluidic model with onthefly machine learning
We present a hybrid continuumatomistic scheme which combines molecular ...
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On the Geometric Ergodicity of Hamiltonian Monte Carlo
We establish general conditions under which Markov chains produced by th...
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Tractable Combinations of Global Constraints
We study the complexity of constraint satisfaction problems involving gl...
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Sampling constrained probability distributions using Spherical Augmentation
Statistical models with constrained probability distributions are abunda...
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FrankWolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees
There is renewed interest in formulating integration as an inference pro...
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Highdimensional Ordinary Leastsquares Projection for Screening Variables
Variable selection is a challenging issue in statistical applications wh...
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University of Warwick
The University of Warwick is one of the UK's leading universities with an acknowledged reputation for excellence in research and teaching, for innovation, and for links with business and industry. Founded in 1965 with an initial intake of 450 undergrad...