University of Reading

research

∙ 07/06/2021

Enabling Un-/Semi-Supervised Machine Learning for MDSE of the Real-World CPS/IoT Applications

In this paper, we propose a novel approach to support domain-specific Mo...

Armin Moin, et al. ∙

research

∙ 09/05/2021

Efficient computation of matrix-vector products with full observation weighting matrices in data assimilation

Recent studies have demonstrated improved skill in numerical weather pre...

Guannan Hu, et al. ∙

research

∙ 05/28/2020

MCMC for Bayesian uncertainty quantification from time-series data

Many problems in science and engineering require uncertainty quantificat...

Philip Maybank, et al. ∙

research

∙ 07/01/2020

Reconstructing regime-dependent causal relationships from observational time series

Inferring causal relations from observational time series data is a key ...

Elena Saggioro, et al. ∙

research

∙ 07/06/2021

A Model-Driven Engineering Approach to Machine Learning and Software Modeling

Models are used in both the Software Engineering (SE) and the Artificial...

Armin Moin, et al. ∙

research

∙ 07/06/2021

ML-Quadrat DriotData: A Model-Driven Engineering Tool and a Low-Code Platform for Smart IoT Services

In this paper, we present the novel early tool prototype of ML-Quadrat, ...

Armin Moin, et al. ∙

research

∙ 07/14/2021

MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence

Over the past decade, Artificial Intelligence (AI) has provided enormous...

Armin Moin, et al. ∙

research

∙ 07/14/2021

A novel approach for modelling and classifying sit-to-stand kinematics using inertial sensors

Sit-to-stand transitions are an important part of activities of daily li...

Maitreyee Wairagkar, et al. ∙

research

∙ 07/30/2021

Distributed Representations of Atoms and Materials for Machine Learning

The use of machine learning is becoming increasingly common in computati...

Luis M. Antunes, et al. ∙

research

∙ 01/17/2020

Bayesian inference of dynamics from partial and noisy observations using data assimilation and machine learning

The reconstruction from observations of high-dimensional chaotic dynamic...

Marc Bocquet, et al. ∙

research

∙ 01/31/2022

Adversarial Robustness in Deep Learning: Attacks on Fragile Neurons

We identify fragile and robust neurons of deep learning architectures us...

Chandresh Pravin, et al. ∙

research

∙ 03/06/2022

Enabling Automated Machine Learning for Model-Driven AI Engineering

Developing smart software services requires both Software Engineering an...

Armin Moin, et al. ∙

research

∙ 04/15/2022

Transfer Learning for Instance Segmentation of Waste Bottles using Mask R-CNN Algorithm

This paper proposes a methodological approach with a transfer learning s...

Punitha Jaikumar, et al. ∙

research

∙ 05/02/2022

TuGeBiC: A Turkish German Bilingual Code-Switching Corpus

In this paper we describe the process of collection, transcription, and ...

Jeanine Treffers-Daller and, et al. ∙

research

∙ 05/23/2022

Regime and Treatment Effects in Duration Models: Decomposing Expectation and Transplant Effects on the Kidney Waitlist

This paper proposes a causal decomposition framework for settings in whi...

Stephen Kastoryano, et al. ∙

research

∙ 06/23/2022

A Bayesian Approach to Atmospheric Circulation Regime Assignment

The standard approach when studying atmospheric circulation regimes and ...

Swinda K. J. Falkena, et al. ∙

research

∙ 09/15/2022

MDE for Machine Learning-Enabled Software Systems: A Case Study and Comparison of MontiAnna ML-Quadrat

In this paper, we propose to adopt the MDE paradigm for the development ...

Jörg Christian Kirchhof, et al. ∙

research

∙ 11/14/2022

Adaptive search space decomposition method for pre- and post- buckling analyses of space truss structures

The paper proposes a novel adaptive search space decomposition method an...

Varun Ojha, et al. ∙

research

∙ 11/09/2018

Precision of the ENDGame: Mixed-precision arithmetic in the iterative solver of the Unified Model

The Met Office's weather and climate simulation code the Unified Model i...

Christopher M Maynard, et al. ∙

research

∙ 04/11/2016

In the mood: the dynamics of collective sentiments on Twitter

We study the relationship between the sentiment levels of Twitter users ...

Nathaniel Charlton, et al. ∙

research

∙ 09/04/2015

l1-norm Penalized Orthogonal Forward Regression

A l1-norm penalized orthogonal forward regression (l1-POFR) algorithm is...

Xia Hong, et al. ∙

research

∙ 04/01/2015

Bayesian model comparison with un-normalised likelihoods

Models for which the likelihood function can be evaluated only up to a p...

Richard G. Everitt, et al. ∙

research

∙ 01/21/2015

Lazier ABC

ABC algorithms involve a large number of simulations from the model of i...

Dennis Prangle, et al. ∙

research

∙ 04/07/2015

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization

Tensors or multiarray data are generalizations of matrices. Tensor clust...

Yanfeng Sun, et al. ∙

research

∙ 07/27/2018

Particle filters for applications in geosciences

Particle filters contain the promise of fully nonlinear data assimilatio...

Peter Jan van Leeuwen, et al. ∙

research

∙ 09/19/2018

LFRic: Meeting the challenges of scalability and performance portability in Weather and Climate models

This paper describes LFRic: the new weather and climate modelling system...

S. V. Adams, et al. ∙

research

∙ 09/25/2018

Perturbation Bounds for Monte Carlo within Metropolis via Restricted Approximations

The Monte Carlo within Metropolis (MCwM) algorithm, interpreted as a per...

Felipe Medina-Aguayo, et al. ∙

research

∙ 11/19/2016

Determining the Veracity of Rumours on Twitter

While social networks can provide an ideal platform for up-to-date infor...

Georgios Giasemidis, et al. ∙

research

∙ 01/24/2019

Modelling the Demand and Uncertainty of Low Voltage Networks and the Effect of non-Domestic Consumers

The increasing use and spread of low carbon technologies are expected to...

Georgios Giasemidis, et al. ∙

research

∙ 01/29/2019

Sparse Least Squares Low Rank Kernel Machines

A general framework of least squares support vector machine with low ran...

Manjing Fang, et al. ∙

research

∙ 06/05/2019

Ensemble MCMC: Accelerating Pseudo-Marginal MCMC for State Space Models using the Ensemble Kalman Filter

Particle Markov chain Monte Carlo (pMCMC) is now a popular method for pe...

Christopher Drovandi, et al. ∙

research

∙ 06/10/2019

Analysis of parallel I/O use on the UK national supercomputing service, ARCHER using Cray LASSi and EPCC SAFE

In this paper, we describe how we have used a combination of the LASSi t...

Andrew Turner, et al. ∙

research

∙ 06/11/2019

Residual estimates for post-processors in elliptic problems

In this work we examine a posteriori error control for post-processed ap...

Andreas Dedner, et al. ∙

research

∙ 08/21/2019

Spectral estimates for saddle point matrices arising in weak constraint four-dimensional variational data assimilation

We consider the large-sparse symmetric linear systems of equations that ...

Ieva Daužickaitė, et al. ∙

research

∙ 11/15/2019

Coupling Matrix Manifolds and Their Applications in Optimal Transport

Optimal transport (OT) is a powerful tool for measuring the distance bet...

Dai Shi, et al. ∙

research

∙ 12/13/2019

Lessons from reinforcement learning for biological representations of space

Neuroscientists postulate 3D representations in the brain in a variety o...

Alex Muryy, et al. ∙

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