Mathematics - 2019

Banks, H. T., & Joyner, M. L. (2019). ADAPTION OF AKAIKE INFORMATION CRITERION UNDER LEAST SQUARES FRAMEWORKS FOR COMPARISON OF STOCHASTIC MODELS. QUARTERLY OF APPLIED MATHEMATICS, 77(4), 831–859. https://doi.org/10.1090/qam/1542

Banks, H. T., Bekele-Maxwell, K., Bociu, L., Noorman, M., & Guidiboni, G. (2019). LOCAL SENSITIVITY VIA THE COMPLEX-STEP DERIVATIVE APPROXIMATION FOR 1D PORO-ELASTIC AND PORO-VISCO-ELASTIC MODELS. MATHEMATICAL CONTROL AND RELATED FIELDS, 9(4), 623–642. https://doi.org/10.3934/mcrf.2019044

Bartels, S., Cockayne, J., Ipsen, I. C. F., & Hennig, P. (2019). Probabilistic linear solvers: a unifying view. STATISTICS AND COMPUTING, 29(6), 1249–1263. https://doi.org/10.1007/s11222-019-09897-7

Butorac, M., Jing, N., & Kozic, S. (2019). h-Adic quantum vertex algebras associated with rational R-matrix in types B, C and D. LETTERS IN MATHEMATICAL PHYSICS, 109(11), 2439–2471. https://doi.org/10.1007/s11005-019-01199-3

Dhole, S., Lloyd, A. L., & Gould, F. (2019). Tethered homing gene drives: A new design for spatially restricted population replacement and suppression. EVOLUTIONARY APPLICATIONS, 12(8), 1688–1702. https://doi.org/10.1111/eva.12827

Farazmand, M., & Sapsis, T. (2019). Surface Waves Enhance Particle Dispersion. Fluids. https://doi.org/10.3390/fluids4010055

Farazmand, M., & Sapsis, T. P. (2019). Extreme Events: Mechanisms and Prediction. Applied Mechanics Reviews, 71(5). https://doi.org/10.1115/1.4042065

Girolami, M., Ipsen, I. C. F., Oates, C. J., Owen, A. B., & Sullivan, T. J. (2019, November). Editorial: special edition on probabilistic numerics. STATISTICS AND COMPUTING, Vol. 29, pp. 1181–1183. https://doi.org/10.1007/s11222-019-09892-y

Heikkola, E., Ito, K., & Toivanen, J. (2019). A PARALLEL DOMAIN DECOMPOSITION METHOD FOR THE HELMHOLTZ EQUATION IN LAYERED MEDIA. SIAM JOURNAL ON SCIENTIFIC COMPUTING, 41(5), C505–C521. https://doi.org/10.1137/18M1230906

Hong, H., Ovchinnikov, A., Pogudin, G., & Yap, C. (2019). SIAN: a tool for assessing structural identifiability of parametric ODEs. ACM COMMUNICATIONS IN COMPUTER ALGEBRA, 53(2), 37–40. https://doi.org/10.1145/3371991.3371993

Hong, H., Ovchinnikov, A., Pogudin, G., & Yap, C. (2019). SIAN: software for structural identifiability analysis of ODE models. BIOINFORMATICS, 35(16), 2873–2874. https://doi.org/10.1093/bioinformatics/bty1069

Igarashi, M., Misra, K. C., & Pongprasert, S. (2019). D-5((1))-Geometric crystal corresponding to the Dynkin spin node i=5 and its ultra-discretization. JOURNAL OF ALGEBRA AND ITS APPLICATIONS, 18(12). https://doi.org/10.1142/S021949881950227X

Morrow, Z., Liu, C., Kelley, C. T., & Jakubikova, E. (2019). Approximating Periodic Potential Energy Surfaces with Sparse Trigonometric Interpolation. The Journal of Physical Chemistry B, 123(45), 9677–9684. https://doi.org/10.1021/acs.jpcb.9b08210

Saibaba, A. K., Bardsley, J., Brown, D. A., & Alexanderian, A. (2019). Efficient Marginalization-Based MCMC Methods for Hierarchical Bayesian Inverse Problems. SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 7(3), 1105–1131. https://doi.org/10.1137/18M1220625

Schacht, C., Meade, A., Banks, H. T., Enderling, H., & Abate-Daga, D. (2019). Estimation of probability distributions of parameters using aggregate population data: analysis of a CAR T-cell cancer model. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 16(6), 7299–7326. https://doi.org/10.3934/mbe.2019365

Sudweeks, J., Hollingsworth, B., Blondel, D. V., Campbell, K. J., Dhole, S., Eisemann, J. D., … Lloyd, A. L. (2019). Locally Fixed Alleles: A method to localize gene drive to island populations. SCIENTIFIC REPORTS, 9, 15821. https://doi.org/10.1038/s41598-019-51994-0

Xiao, Y., Guo, C., Meng, F., Jing, N., & Yung, M.-H. (2019). Incompatibility of observables as state-independent bound of uncertainty relations. PHYSICAL REVIEW A, 100(3). https://doi.org/10.1103/PhysRevA.100.032118

Yao, Y., Zhang, Y., Tian, L., Zhou, N., Li, Z., & Wang, M. (2019). Analysis of Network Structure of Urban Bike-Sharing System: A Case Study Based on Real-Time Data of a Public Bicycle System. SUSTAINABILITY, 11(19). https://doi.org/10.3390/su11195425

Yu, B., Jing, N., & Li-Jost, X. (2019). Distribution of spin correlation strengths in multipartite systems. QUANTUM INFORMATION PROCESSING, 18(11). https://doi.org/10.1007/s11128-019-2458-4

Zhao, J. Y., Zhao, H., Jing, N., & Fei, S.-M. (2019). Detection of Genuine Multipartite Entanglement in Multipartite Systems. INTERNATIONAL JOURNAL OF THEORETICAL PHYSICS, 58(10), 3181–3191. https://doi.org/10.1007/s10773-019-04193-6