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Acko, B.; Weber, H.; Hutzschenreuter, D.; Smith, I. (2020) Communication and validation of metrological smart data in IoT-networks. Advances in Production Engineering & Management, 15 (1). pp. 107-117. ISSN 18546250
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Bilson, S; Thompson, A; Tucker, D; Pearce, J (2023) A machine learning approach to automation and uncertainty evaluation for self-validating thermocouples. NIST Special Publication, 2100 (05). p. 85.
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Chretien, S; Tyagi, H (2020) Multi-kernel Unmixing and Super-Resolution Using the Modified Matrix Pencil Method. Journal of Fourier Analysis and Applications, 26 (1). 18 ISSN 1069-5869
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Cox, M G; Dainton, M P; Harris, P M (2000) Testing functions for linear regression. NPL Report. CMSC 08/00
Cox, M G; Dainton, M P; Harris, P M (2000) Testing functions for the calculation of standard deviation. NPL Report. CMSC 07/00
Cox, M G; Dainton, M P; Harris, P M (2001) Testing the numerical correctness of software for the calculation of sample standard deviation. In: National Measurement Conference (NMC) 2001, 6-8 November 2001, Harrogate, UK.
Cox, M G; Forbes, A B (1999) Strategies for testing form assessment software. NPL Report. DITC 211/92
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Cox, M G; Harris, P M; Johnson, E G; Kenward, P D; Parkin, G I (2004) Testing the numerical correctness of software. NPL Report. CMSC 34/04
Cox, M G; Harris, P M; Kenward, P D; Smith, I M (2004) Exploratory data analysis. NPL Report. CMSC 47/04
Cox, M G; Rossi, G B*; Harris, P M; Forbes, A B (2009) Reply to the comment on 'A probabilistic approach to the analysis of measurement processes'. Metrologia, 46 (1). L9-L10
Cox, M G; Shirono, K* (2017) Informative Bayesian Type A uncertainty evaluation for a small number of observations. Metrologia, 54 (5). pp. 642-652.
Dong, H Y; Butler, K T; Matras, D; Price, S W T; Odarchenko, Y; Khatry, R; Thompson, A; Middelkoop, V; Jacques, S D M; Beale, A M; Vamvakeros, A (2021) A deep convolutional neural network for real-time full profile analysis of big powder diffraction data. npj Computational Materials, 7 (1). 74
Eftekhari, A; Tanner, J; Thompson, A; Toader, B; Tyagi, H (2021) Sparse non-negative super-resolution — simplified and stabilised. Applied and Computational Harmonic Analysis, 50. pp. 216-280. ISSN 10635203
Eftekhari, A; Thompson, A (2019) Sparse Inverse Problems over Measures: Equivalence of the Conditional Gradient and Exchange Methods. SIAM Journal on Optimization, 29 (2). pp. 1329-1349. ISSN 1052-6234
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Gandomi, A H*; Yang, X-S; Alavi, A H* (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Eng. Comput., 29 (1). pp. 17-35.
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Gandomi, A H*; Yang, X-S; Alavi, A H*; Talatahari, S* (2013) Bat algorithm for constrained optimization tasks. Neural Comput. App, 22 (6). pp. 1239-1255.
Harris, P M (2015) Traceability for computationally-intensive metrology: benchmark reference pairs for measurement uncertainty evaluation. NPL Report. MS 17
Harris, P M (2015) Traceability for computationally-intensive metrology: benchmark reference pairs for principal components analysis. NPL Report. MS 18
Harris, P M; Lines, K J; Smith, I M (2006) Testing the numerical correctness of software. NPL Report. DEM-ES 004
Harris, P M; Smith, I M (2004) Testing algorithms for free-knot spline approximation. NPL Report. CMSC 48/04
Ivander, F; Lindoy, L P; Lee, J (2024) Unified Framework for Open Quantum Dynamics with Memory. Nature Communications, 15. 8087
Jagan, K; Forbes, A (2018) Analysis of measurement data subject to additive and multiplicative effects. Journal of Physics: Conference Series, 1065. 212024 ISSN 1742-6588
Jagan, K; Forbes, A B (2018) NLLSMH: MCMC software for nonlinear least squares regression. In: Advanced Mathematical and Computational Tools in Metrology and Testing XI. World Scientific Publishing, pp. 211-219. ISBN 9789813274297
Khatry, R; Thompson, A (2021) Good practice in training set preparation for marine navigation systems. NPL Report. MS 33
Kok, G; Harris, P (2020) Quantifying Metrological Redundancy in an Industry 4.0 Environment. In: 2020 IEEE International Workshop on Metrology for Industry 4.0 & IOT (METROIND4.0&IOT), 3 - 5 June 2020, Roma, Italy.
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Lehnert, J; Wübbeler, G; Kolbitsch, C; Chiribiri, A; Coquelin, L; Ebrard, G; Smith, N; Schaeffter, T; Elster, C (2018) Pixel-wise quantification of myocardial perfusion using spatial Tikhonov regularization. Physics in Medicine & Biology, 63 (21). 215017 ISSN 1361-6560
Levene, M; Wooldridge, J (2023) Certification of Machine Learning Applications in the Context of Trustworthy AI with Reference to the Standardisation of AI Systems. NPL Report. MS 45
Lines, K J; Onakunle, F O; Smith, I M (2007) Testing functions for calculating the discrete Fourier transform and its inverse. NPL Report. DEM-ES 016
Markov, V; Mei, S; Salomé, P; Combes, F; Stern, D; Galametz, A; De Breuck, C; Wylezalek, D; Amodeo, S; Cooke, E A; Gonzalez, A H; Hatch, N A; Noirot, G; Rettura, A; Seymour, N; Stanford, S A; Vernet, J (2020) Massive molecular gas reservoir around the central AGN in the CARLA J1103 + 3449 cluster at z = 1.44. Astronomy & Astrophysics, 641. A22 ISSN 0004-6361
Matar, J; El Khoury, H; Charr, J C; Guyeux, C; Chretien, S (2019) SpCLUST: Towards a fast and reliable clustering for potentially divergent biological sequences. Computers in Biology and Medicine, 114. 103439 ISSN 00104825
Mazin, A*; Nabaei, V*; Kazakova, O (2012) Modelling and optimization of submicron Hall sensors for the detection of superparamagnetic beads. J. Appl. Phys., 111 (7). 07E513
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Nguyen, H; Ng, N; Lindoy, L; Park, G; Millis, A J; Chan, G K L; Reichman, D R (2024) Correlation Functions From Tensor Network Influence Functionals: The Case of the Spin-Boson Model. The Journal of Chemical Physics, 161 (10). 104111
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Shelley, L.; Noble, D.; Romanchikova, M.; Harrison, K.; Bates, A.; Sutcliffe, M.; Thomas, S.; Burnet, N.; Jena, R. (2019) PO-0983 Accumulating delivered dose to the rectum using finite element analysis improves toxicity prediction. Radiotherapy and Oncology, 133. S538-S539. ISSN 01678140
Soundaranathan, M; Vivattanaseth, P; Walsh, E; Pitt, K; Johnston, B; Markl, D (2020) Quantification of swelling characteristics of pharmaceutical particles. International Journal of Pharmaceutics, 590. 119903 ISSN 03785173
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Thompson, A; Jagan, K; Sundar, A; Khatry, R; Donlevy, J; Thomas, S; Harris, P (2021) Uncertainty evaluation for machine learning. NPL Report. MS 34
Todhunter, L; Leach, R; Lawes, S; Harris, P; Blateyron, François (2019) Mathematical approach to the validation of functional surface texture parameter software. Surface Topography: Metrology and Properties, 7 (1). 015020 ISSN 2051-672X
Todhunter, L; Leach, R; Lawes, S; Harris, P M; Blateyron, F (2020) Mathematical approach to the validation of field surface texture parameter software. Surface Topography: Metrology and Properties, 8 (1). 015010 ISSN 2051-672X
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