Catherine Higham
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Deep learning: An introduction for applied mathematicians
CF Higham, DJ Higham
Siam review 61 (4), 860-891, 2019
Deep learning for real-time single-pixel video
CF Higham, R Murray-Smith, MJ Padgett, MP Edgar
Scientific reports 8 (1), 2369, 2018
Somatic instability of the expanded CTG triplet repeat in myotonic dystrophy type 1 is a heritable quantitative trait and modifier of disease severity
F Morales, JM Couto, CF Higham, G Hogg, P Cuenca, C Braida, ...
Human molecular genetics 21 (16), 3558-3567, 2012
Neural network identification of people hidden from view with a single-pixel, single-photon detector
P Caramazza, A Boccolini, D Buschek, M Hullin, CF Higham, ...
Scientific reports 8 (1), 11945, 2018
Deep learning optimized single-pixel LiDAR
N Radwell, SD Johnson, MP Edgar, CF Higham, R Murray-Smith, ...
Applied Physics Letters 115 (23), 2019
High levels of somatic DNA diversity at the myotonic dystrophy type 1 locus are driven by ultra-frequent expansion and contraction mutations
CF Higham, F Morales, CA Cobbold, DT Haydon, DG Monckton
Human Molecular Genetics 21 (11), 2450-2463, 2012
Controversy in mechanistic modelling with Gaussian processes
B Macdonald, C Higham, D Husmeier
International conference on machine learning, 1539-1547, 2015
Modelling and inference reveal nonlinear length-dependent suppression of somatic instability for small disease associated alleles in myotonic dystrophy type 1 and Huntington …
CF Higham, DG Monckton
Journal of The Royal Society Interface 10 (88), 20130605, 2013
Detection, identification, and tracking of objects hidden from view with neural networks
G Musarra, P Caramazza, A Turpin, A Lyons, CF Higham, R Murray-Smith, ...
Advanced Photon Counting Techniques XIII 10978, 1097803, 2019
A Bayesian approach for parameter estimation in the extended clock gene circuit of Arabidopsis thaliana
CF Higham, D Husmeier
BMC bioinformatics 14 (Suppl 10), S3, 2013
Bifurcation analysis informs Bayesian inference in the Hes1 feedback loop
CF Higham
BMC systems biology 3, 1-14, 2009
Controversy in mechanistic modemodel with gaussian processes
B Macdonald, CF Higham, D Husmeier
International Conference on Machine Learning (ICML) 54, 70, 2015
Quantum deep learning by sampling neural nets with a quantum annealer
CF Higham, A Bedford
Scientific reports 13 (1), 3939, 2023
Testing a QUBO formulation of core-periphery partitioning on a quantum annealer
CF Higham, DJ Higham, F Tudisco
arXiv preprint arXiv:2201.01543, 2022
Single-pixel LIDAR with deep learning optimised sampling
SD Johnson, N Radwell, MP Edgar, C Higham, R Murray-Smith, ...
2020 Conference on Lasers and Electro-Optics (CLEO), 1-2, 2020
Dynamic DNA and human disease: mathematical modelling and statistical inference for myotonic dystrophy type 1 and Huntington disease
CF Higham
University of Glasgow, 2013
Core-periphery partitioning and quantum annealing
CF Higham, DJ Higham, F Tudisco
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
Individual variation in the structure of bilingual grammars
C Cohen, SW Nabi, CF Higham, M Putnam, GJ Kootstra, JG van Hell
Language 97 (4), 752-792, 2021
Deep Learnability: Using Neural Networks to Quantify Language Similarity and Learnability
C Cohen, CF Higham, SW Nabi
Frontiers in Artificial Intelligence 3, 43, 2020
School of Computing Science
I Ounis, R Murray-Smith, J Jose, C MacDonald, N Pugeault, P Siebert, ...
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