Number of items: 17.
2023
Fang, Y., Niu, M., Cheung, P. and Lin, L.
(2023)
Extrinsic Bayesian optimization on manifolds.
Algorithms, 16(2),
117.
(doi: 10.3390/a16020117)
Niu, M., Dai, Z., Cheung, P. and Wang, Y.
(2023)
Intrinsic Gaussian process on unknown manifolds with probabilistic metrics.
Journal of Machine Learning Research, 24(104),
pp. 1-42.
2022
Szili, B., Niu, M. and Neocleous, T.
(2022)
A Structural Learning Method for Graphical Models.
In: 4th International Conference on Statistics: Theory and Applications (ICSTA'22), Prague, Czech Republic, 28-30 Jul 2022,
p. 113.
ISBN 9781990800085
(doi: 10.11159/icsta22.113)
Niu, M., Frost, F., Milner, J. E., Skarin, A. and Blackwell, P. G.
(2022)
Modelling group movement with behaviour switching in continuous time.
Biometrics, 78(1),
pp. 286-299.
(doi: 10.1111/biom.13412)
(PMID:33270218)
2021
Niu, M., Wandy, J. , Daly, R. , Rogers, S. and Husmeier, D.
(2021)
R package for statistical inference in dynamical systems using kernel based gradient matching: KGode.
Computational Statistics, 36(1),
pp. 715-747.
(doi: 10.1007/s00180-020-01014-x)
Milner, J. E., Blackwell, P. G. and Niu, M.
(2021)
Modelling and inference for the movement of interacting animals.
Methods in Ecology and Evolution, 12(1),
pp. 54-69.
(doi: 10.1111/2041-210X.13468)
2019
Niu, M., Cheung, P., Lin, L., Dai, Z., Lawrence, N. and Dunson, D.
(2019)
Intrinsic Gaussian processes on complex constrained domains.
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 81(3),
pp. 603-627.
(doi: 10.1111/rssb.12320)
Lin, L., Niu, M., Cheung, P. and Dunson, D.
(2019)
Extrinsic Gaussian processes for regression and classification on manifolds.
Bayesian Analysis, 14(3),
pp. 887-906.
(doi: 10.1214/18-BA1135)
2018
Niu, M., Macdonald, B. , Rogers, S. , Filippone, M. and Husmeier, D.
(2018)
Statistical inference in mechanistic models: time warping for improved gradient matching.
Computational Statistics, 33(2),
pp. 1091-1123.
(doi: 10.1007/s00180-017-0753-z)
2017
Niu, M., Rogers, S. , Filippone, M. and Husmeier, D.
(2017)
Parameter Inference in Differential Equation Models Using Time Warped Gradient Matching.
RSS 2017 Annual Conference, Glasgow, Scotland, 04-07 Sep 2017.
Niu, M., Rogers, S. , Filippone, M. and Husmeier, D.
(2017)
Parameter Inference in Differential Equation Models of
Biopathways using Time Warped Gradient Matching.
In: 13th International Conference on Computational Intelligence Methods for Bioinformatics and Biostatistics, Stirling, UK, 01-03 Sep 2016,
pp. 145-159.
ISBN 9783319678337
(doi: 10.1007/978-3-319-67834-4_12)
2016
Macdonald, B., Niu, M., Rogers, S. , Filippone, M. and Husmeier, D.
(2016)
Approximate parameter inference in systems biology using gradient matching: a comparative evaluation.
BioMedical Engineering OnLine, 15,
80.
(doi: 10.1186/s12938-016-0186-x)
(PMID:27454253)
(PMCID:PMC4959362)
Niu, M., Rogers, S. , Filippone, M. and Husmeier, D.
(2016)
Fast inference in nonlinear dynamical systems using gradient matching.
Proceedings of Machine Learning Research, 48,
pp. 1699-1707.
Niu, M., Blackwell, P. G. and Skarin, A.
(2016)
Modeling interdependent animal movement in continuous time.
Biometrics, 72(2),
pp. 315-324.
(doi: 10.1111/biom.12454)
(PMID:26812666)
Blackwell, P. G., Niu, M., Lambert, M. S., LaPoint, S. D. and O'Hara, R. B.
(2016)
Exact Bayesian inference for animal movement in continuous time.
Methods in Ecology and Evolution, 7(2),
pp. 184-195.
(doi: 10.1111/2041-210X.12460)
2015
Niu, M., Filippone, M., Husmeier, D. and Rogers, S.
(2015)
Inference in Nonlinear Differential Equations.
In: 30th International Workshop on Statistical Modelling, Linz, Austria, 06-10 Jul 2015,
pp. 187-190.
2013
Reimer, P. J. et al.
(2013)
IntCal13 and Marine13 Radiocarbon Age Calibration Curves 0–50,000 Years cal BP.
Radiocarbon, 55(4),
pp. 1869-1887.
(doi: 10.2458/azu_js_rc.55.16947)
This list was generated on Thu Apr 18 13:22:45 2024 BST.
