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Proceedings

Papers

  1. H. Ikebata, R. Yoshida,
    Repulsive parallel MCMC algorithm for discovering diverse motifs from large sequence sets,
    Bioinformatics, Vol. 31(10), pp. 1561-1568, 2015.
  2. T. Tokunaga, O. Hirose, S. Kawaguchi, Y. Toyoshima, T. Teramoto, H. Ikebata, S. Kuge, T. Ishihara, Y. Iino, R. Yoshida,
    Automated detection and tracking of many cells by using 4D live-cell imaging data,
    Bioinformatics, Vol. 30(12), i43-i51, 2014.
  3. H. Yamashita, T. Higuchi, R. Yoshida,
    Atom Environment Kernels on Molecules,
    J. Chem. Inf. Model, doi:10.1021/ci400403w, 2014.
  4. S. Nakano, M.-C. Fok, P. C. Brandt, and T. Higuchi,
    Estimation of the helium ion density distribution in the plasmasphere based on a single IMAGE/EUV image,
    J. Geophys. Res., Vol. 119, pp. 3724-3740, doi:10.1002/2013JA019733, 2014.
  5. S. Nakano, M.-C. Fok, P. C. Brandt, and T. Higuchi,
    Estimation of temporal evolution of the helium plasmasphere based on a sequence of IMAGE/EUV images,
    J. Geophys. Res., Vol. 119, pp. 3708-3723, doi:10.1002/2013JA019734, 2014.
  6. S. Nakano,
    Hybrid algorithm of ensemble transform and importance sampling for assimilation of non-Gaussian observations,
    Tellus A, Vol. 66, 21429, doi:10.3402/tellusa.v66.21429, 2014.
  7. G. Ueno and N. Nakamura,
    Iterative algorithm for maximum-likelihood estimation of the observation-error covariancematrix for ensemble-based filters,
    Quarterly Journal of the Royal Meteorological Society, Vol. 140, pp. 295-315, doi:10.1002/qj.2134, 2014.
  8. M. M. Saito, S. Imoto, R. Yamaguchi, M. Tsubokura, M. Kami, H. Nakada, H. Sato, S. Miyano, T. Higuchi,
    Enhancement of Collective Immunity in Tokyo Metropolitan Area by Selective Vaccination against an Emerging Influenza Pandemic,
    PLoS ONE, Vol. 8(9), e72866, doi:10.1371/journal.pone.0072866, 2013.
  9. M. M. Saito, S. Imoto, R. Yamaguchi, M. Kami, H. Nakada, H. Sato, S. Miyano, T. Higuchi,
    Extension and verification of the SEIR model on the 2009 influenza A (H1N1) pandemic in Japan,
    Mathematical Biosciences, Vol. 246(1), pp. 47-54, 2013.
  10. H. Nagao, T. Higuchi, S. Miura, and D. Inazu,
    Time-series modeling of tide gauge records for monitoring of the crustal activities related to oceanic trench earthquakes around Japan,
    The Computer Journal, doi:10.1093/comjnl/bxs139, 2012.
  11. S. Nakano and T. Higuchi,
    Non-storm irregular variation of the Dst index,
    Annales Geophysicae, vol. 30, pp. 153-162, 2012.
  12. S. Saita, A. Kadokura, N. Sato, S. Fujita, T. Tanaka, Y. Ebihara, S. Ohtani, G. Ueno, K. Murata, D. Matsuoka, A. Kitamoto, and T. Higuchi,
    Displacement of conjugate points during a substorm in a global magnetohydrodynamic simulation,
    Journal of Geophysical Research, Vol. 116, A06213, doi:10.1029/2010JA016155, 2011.
  13. T. Ishigaki, T. Higuchi, and K. Watanabe,
    Fault detection of a vibration mechanism by spectrum classification with a divergence-based kernel,
    IET Signal Processing, Vol. 4, Iss. 5, 518-529, doi:10.1049/iet-spr.2008.0195, 2010.
  14. R. Yoshida, M.M. Saito, H. Nagao, and T. Higuchi,
    Bayesian experts in exploring reaction kinetics of transcription circuits,
    Bioinformatics, Vol. 26, i589-i595, 2010.
  15. G. Ueno, T. Higuchi, T. Kagimoto, N. Hirose,
    Maximum likelihood estimation of error covariances in ensemble-based filters and its application to a coupled atmosphere-ocean model,
    Quarterly Journal of the Royal Meteorological Society, Vol.136, 1316-1343, DOI:10.1002/qj.654, 2010.
  16. D. Inazu, T. Higuchi, K. Nakamura,
    Optimization of boundary condition and physical parameter in an ocean tide model using an evolutionary algorithm,
    Theoretical and Applied Mechanics Japan, Vol. 58, 101-112, 2009.
  17. S. Nakano and T. Higuchi,
    Estimation of a long-term variation of a magnetic- storm index using the merging particle filter,
    IEICE Trans. Inf. Syst., Vol. E92-D, No.7, pp. 1382-1387, 2009.   >>
  18. G. Ueno and T. Tsuchiya,
    Covariance regularization in inverse space,
    Quarterly Journal of the Royal Meteorological Society, Vol. 135, pp. 1133-1156, 2009. [PDF]
  19. D. Inazu, T. Sato, S. Miura, Y. Ohta, K. Nakamura, H, Fujimoto, C. F. Larsen, and T. Higuchi,
    Accurate ocean tide modeling in southeast Alaska and large tidal dissipation around Glacier Bay,
    Journal of Oceanography, Vol. 65, No. 3, pp. 335-347, 2009.
  20. K. Nakamura, N. Hirose, B. H. Choi, and T. Higuchi,
    Particle filtering in data assimilation and its application to boundary condition of tsunami simulation model,
    Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications, edited by S. K. Park and L. Xu, pp. 353-366, Springer, 2009.
  21. S. Nakano, G. Ueno, S. Ohtani, and T. Higuchi,
    Impact of the solar-wind dynamic pressure on the Region-2 field-aligned currents,
    Journal of Geophysical Research, Vol. 114, A02221, doi:10.1029/2008JA013674, 2009.
  22. R. Yoshida, M. Nagasaki, R. Yamaguchi, S. Imoto, S. Miyano, and T. Higuchi,
    Bayesian learning of biological pathways on genomic data assimilation,
    Bioinformatics, Vol. 24, No. 22, 2592-2601, 2008.
  23. S. Nakano, G. Ueno, Y. Ebihara, M.-C. Fok, S. Ohtani, P. C. Brandt, D. G. Mitchell, K. Keika, and T. Higuchi,
    A method for estimating the ring current structure and the electric potential distribution using ENA data assimilation,
    Journal of Geophysical Research, Vol. 113, A05208, doi:10.1029/2006JA011853, 2008.   >>
  24. J. Fukuda, S. Miyazaki, T. Higuchi, and T. Kato,
    Geodetic inversion for space-time distribution of fault slip with time-varying smoothing regularization,
    Geophysical Journal International, Vol. 173, pp. 25-48, 2008.
  25. S. Nakano, G. Ueno, and T. Higuchi,
    Merging particle filter for sequential data assimilation,
    Nonlinear Processes in Geophysics, Vol. 14, pp. 395-408, 2007. [PDF]
  26. G. Ueno, T. Higuchi, T. Kagimoto, and N. Hirose,
    Application of the ensemble Kalman filter and smoother to a coupled atmosphere-ocean model,
    Scientific Online Letters on the Atmosphere, Vol. 3, pp. 5-8, 2007. [PDF]

Proceedings (refereed)

  1. M. M. Saito, S. Imoto, R. Yamaguchi, S. Miyano, T. Higuchi,
    Parameter estimation in multi-compartment SIR model,
    Proceedings of 17th International Conference on Information Fusion, 2014.
  2. H. Nagao and T. Higuchi,
    Data assimilation system for seismoacoustic waves,
    Proceedings of 16th International Conference on Information Fusion, 2013.
  3. M. M. Saito, S. Imoto, R. Yamaguchi, S. Miyano, T. Higuchi,
    Estimation of abrupt changes in sentinel observation data of influenza epidemics in Japan,
    Proceedings of 16th International Conference on Information Fusion, 2013.
  4. S. Nakano,
    A prediction algorithm with a limited number of particles for state estimation of high-dimensional systems,
    Proceedings of 16th International Conference on Information Fusion, pp. 1356-1363, 2013.
  5. M. M. Saito, S. Imoto, R. Yamaguchi, S. Miyano, T. Higuchi,
    Identifiability of local transmissibility parameters in agent-based pandemic simulation,
    Proceedings of 15th International Conference on Information Fusion, 2012.
  6. H. Nagao and T. Higuchi,
    Data assimilation of the earth's atmospheric and ionospheric oscillations excited by large earthquakes,
    Proceedings of 15th International Conference on Information Fusion, 2012.
  7. S. Nakano and T. Higuchi,
    Weight adjustment of the particle filter on distributed computing systems,
    Proceedings of 15th International Conference on Information Fusion, 2012.
  8. T. Higuchi,
    Embedding reality in a numerical simulation with data assimilation,
    Proceedings of 14th International Conference Fusion, 2011.
  9. H. Nagao, N. Kobayashi, S. Nakano and T. Higuchi,
    Fault parameter estimation with data assimilation on infrasound variations due to big earthquakes,
    Proceedings of 14th International Conference Fusion, 2011.
  10. M. M. Saito, S. Imoto, R. Yamaguchi, S. Miyano and T. Higuchi,
    Estimation of macroscopic parameter in agent-based pandemic simulation,
    Proceedings of 14th International Conference Fusion, 2011.
  11. K. Hayashi, M. M. Saito, R. Yoshida, T. Higuchi,
    Implementation of Sequential Importance Sampling in GPGPU,
    Proceedings of the 13th International Conference on Information Fusion, 2010.
  12. H. Nagao, and T. Higuchi,
    Web application for time-series analysis based on particle filter available on cloud computing system,
    Proceedings of the 13th International Conference on Information Fusion, 2010.
  13. S. Nakano, and T. Higuchi,
    A dynamic grouping strategy for implementation of the particle filter on a massively parallel computer,
    Proceedings of the 13th International Conference on Information Fusion, 2010.
  14. S. Nakano,
    Population-based quasi-Bayesian algorithm for high-dimensional sequential problems and hierarchization of it for distributed computing environments,
    Proceedings of 2010 IEEE Congress on Evolutionary Computation, doi:10.1109/CEC.2010.5586535, 2010.
  15. K. Nakamura, R. Yoshida, M. Nagasaki, S. Miyano, and T. Higuchi,
    Parameter Estimation of In Silico Biological Pathways with Particle Filtering Towards a Petascale Computing,
    The Proceedings of 14th Pacific Symposium on Biocomputing, 227-238, 2009.
  16. T. Ishigaki, and T. Higuchi,
    Dynamic Spectrum Classification by Divergence-Based Kernel Machines and Its Application to the Detection of Worn-out banknotes,
    The Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE ICASSP 2008), 1873-1876, 2008.
  17. T. Ishigaki, and T. Higuchi,
    Parameter identification of a pressure regulator with a nonlinear structure using a particle filter based on the nonlinear state space model,
    The Proceedings of 11th International Conference of Fusion, 886-891, 2008.
  18. G. Ueno, T. Higuchi, T. Kagimoto, and N. Hirose,
    Prediction of ocean state by data assimilation with the ensemble Kalman filter,
    SCIS&ISIS 2006, 2006. [PDF]
  19. K. Nakamura, T. Higuchi, and N. Hirose,
    Application of Particle Filter to Identification of Tsunami Simulation Model,
    SCIS&ISIS 2006, 2006. [PDF]
  20. T. Higuchi and J. Fukuda,
    Monte Carlo Mixture Kalman filter and its application to GPS data analysis for spase-time inversion,
    13th IFAC Symposium on System Identification, 1299-1304, 2003.