Projects per year
Organization profile
Organisation profile
The Centre for Mathematics and Algorithms for Data (MAD) at the University of Bath is an interdisciplinary group of researchers working at the intersection of Statistics, Machine Learning and Numerical Analysis with a huge range of application areas. Data Scientists use mathematics and computation to extract useful information from data. MAD aims to facilitate dialogue between groups, especially theorists in computer science and mathematics, and develop rigour in the field.
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Dive into the research topics where Centre for Mathematics and Algorithms for Data (MAD) is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.
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Recent external collaboration on country level. Dive into details by clicking on the dots.
Profiles
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Neill Campbell
- Department of Computer Science - Reader
- Centre for the Analysis of Motion, Entertainment Research & Applications
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- UKRI CDT in Accountable, Responsible and Transparent AI
- Centre for Autonomous Robotics (CENTAUR)
- Centre for Mathematics and Algorithms for Data (MAD)
Person: Research & Teaching
Projects
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Estimating under-five mortality rates in space and time in a developing world context using age-period-cohort models
Smith, T., Gascoigne, C. & Wakefield, J.
1/05/20 → 31/12/21
Project: Research-related funding
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Fuzzy cognitive mapping of large-scale brain networks
30/09/19 → 31/08/20
Project: Research-related funding
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Modelling and optimisation of human movement in sporting activities.
Cazzola, D., Haralabidis, N., Serrancoli, G. & Campbell, N.
1/09/18 → 31/08/19
Project: Other
Research Output
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Accelerating Variance-Reduced Stochastic Gradient Methods
Driggs, D., Ehrhardt, M. J. & Schönlieb, C-B., 15 Sep 2020, In: Mathematical Programming.Research output: Contribution to journal › Article › peer-review
Open AccessFile4 Downloads (Pure) -
Active Latent Space Shape Model: A Bayesian Treatment of Shape Model Adaptation with an Application to Psoriatic Arthritis Radiographs
Rambojun, A., Tillett, W., Shardlow, T. & Campbell, N., 3 Nov 2020, (Acceptance date) 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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A low-rank tensor method for PDE-constrained optimization with isogeometric analysis
Bunger, A., Dolgov, S. & Stoll, M., 2020, In: SIAM Journal on Scientific Computing. 42, 1, p. A140-A161 22 p.Research output: Contribution to journal › Article › peer-review
Open Access
Datasets
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Dataset for "Comparison of the within-reader and inter-vendor agreement of left ventricular circumferential strains and volume indices derived from cardiovascular magnetic resonance imaging"
Cookson, A. (Creator), Odunmbaku-Mansell, D. (Creator), Fraser, K. (Creator), Gill, R. (Creator), Raimondo, A. (Creator), Domenico, B. (Creator), Frank, E. (Contributor), Kelly, N. (Contributor), Agostinho Hernandez, B. (Contributor), Fletcher, J. (Contributor), Bartlett, J. (Contributor), Sammut, E. (Contributor), Johnson, T. (Contributor) & Chiribiri, A. (Contributor), University of Bath, 15 Dec 2020
DOI: 10.15125/BATH-00890
Dataset