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Cantab Capital Institute for the Mathematics of Information

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  • Currently displaying 361 - 380 of 2243 publications
Scanning electron diffraction tomography of strain
R Tovey, DN Johnstone, SM Collins, WRB Lionheart, PA Midgley, M Benning, C-B Schönlieb
– Inverse Problems
(2020)
37,
015003
Partial associativity and rough approximate groups
WT Gowers, J Long
– Geometric and Functional Analysis
(2020)
30,
1583
The effect of double diffusion on the dynamics of horizontal turbulent thermohaline jets
M Dadonau, JL Partridge, PF Linden
– Journal of Fluid Mechanics
(2020)
905,
a23
Toy models of top down causation
A Kent
– Entropy (Basel, Switzerland)
(2020)
22,
E1224
Preface for the special issue ‘Variational methods and effective algorithms for imaging and vision’
CB Schonlieb, M Hintermuller, S Arridge
– Inverse Problems
(2020)
36,
110401
Counting the Costs of COVID-19: Why Future Treatment Option Values Matter
A Kent
– Applied Economics and Finance
(2020)
7,
36
Displacement ventilation: A viable ventilation strategy for makeshift hospitals and public buildings to contain COVID-19 and other airborne diseases: Ventilation strategy for COVID-19
RK Bhagat, PF Linden
– R Soc Open Sci
(2020)
7,
200680
Effects of ventilation on the indoor spread of COVID-19.
RK Bhagat, MS Davies Wykes, SB Dalziel, PF Linden
– Journal of fluid mechanics
(2020)
903,
F1
Consistent Inversion of Noisy Non-Abelian X-Ray Transforms
F Monard, R Nickl, GP Paternain
– Communications on Pure and Applied Mathematics
(2020)
74,
1045
Experimental study on low-speed streaks in a turbulent boundary layer at low Reynolds number
XY Jiang, CB Lee, CR Smith, JW Chen, PF Linden
– Journal of Fluid Mechanics
(2020)
903,
a6
The dynamics of stratified horizontal shear flows at low Peclet number
L Cope, P Garaud, CP Caulfield
– Journal of Fluid Mechanics
(2020)
903,
a1
Accelerating variance-reduced stochastic gradient methods
D Driggs, MJ Ehrhardt, CB Schönlieb
– Mathematical Programming
(2020)
191,
671
IUNets: Learnable invertible up-and downsampling for large-scale inverse problems
C Etmann, R Ke, CB Schonlieb
– IEEE International Workshop on Machine Learning for Signal Processing, MLSP
(2020)
2020-September,
1
A quantitative framework for exploring exit strategies from the COVID-19 lockdown.
AS Fokas, J Cuevas-Maraver, PG Kevrekidis
– Chaos, Solitons & Fractals
(2020)
140,
110244
Time‐Lapse Acoustic Imaging of Mesoscale and Fine‐Scale Variability within the Faroe‐Shetland Channel
A Dickinson, NJ White, CP Caulfield
– Journal of Geophysical Research: Oceans
(2020)
125,
ARTN e2019JC015861
Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem
M Giordano, R Nickl
– Inverse Problems
(2020)
36,
085001
Representation and reconstruction of covariance operators in linear inverse problems
E Lila, S Arridge, JAD Aston
– Inverse Problems
(2020)
36,
085002
A bilinear version of Bogolyubov’s theorem
WT Gowers, L Milicevic
– Proceedings of the American Mathematical Society
(2020)
148,
4695
The circular capillary jump
RK Bhagat, PF Linden
– Journal of Fluid Mechanics
(2020)
896,
a25
Mathematical models and deep learning for predicting the number of individuals reported to be infected with SARS-CoV-2.
AS Fokas, N Dikaios, GA Kastis
– Journal of the Royal Society Interface
(2020)
17,
20200494