Papers

Y. Ogata and T. Omi,

"Statistical Monitoring and Early Forecasting of the Earthquake Sequence: Case Studies after the 2019 M 6.4 Searles Valley Earthquake, California",

Bulletin of the Seismological Society of America 110, 1781–1798 (2020). [Journal]

T. Omi, N. Ueda, and K. Aihara,

"Fully neural network based model for general temporal point processes",

Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 2120 (2019). [Paper] [arXiv] [Software]

(Acceptance rate: 21.2%, 1428/6734)

T. Omi, Y. Ogata, K. Shiomi, B. Enescu, K. Sawazaki, and K. Aihara,

"Implementation of a real-time system for automatic aftershock forecasting in Japan",

Seismological Research Letters 90, 242 (2018). [PDF] [Journal]

T. Omi, Y. Hirata, and K. Aihara,

"Hawkes process model with a time-dependent background rate and its application to high-frequency financial data",

Physical Review E 96, 012303 (2017). [PDF] [Journal] [Software]

T. Omi, Y. Ogata, K. Shiomi, B. Enescu, K. Sawazaki, and K. Aihara,

"Automatic aftershock forecasting: A test using real-time seismicity data in Japan",

Bulletin of the Seismological Society of America 106, 2450 (2016). [PDF] [Journal]

T. Omi, Y. Ogata, Y. Hirata, and K. Aihara,

"Intermediate-term forecasting of aftershocks from an early aftershock sequence: Bayesian and ensemble forecasting approaches",

Journal of Geophysical Research: Solid Earth 120, 2561 (2015). [PDF] [Journal]

T. Omi, Y. Ogata, Y. Hirata, and K. Aihara,

"Estimating the ETAS model from an early aftershock sequence", [Open Access]

Geophysical Research Letters 41, 850 (2014). [PDF] [Journal]

T. Omi, Y. Ogata, Y. Hirata, and K. Aihara,

"Forecasting large aftershocks within one day after the main shock", [Open Access]

Scientific Reports 3, 2218 (2013). [PDF] [Journal] [Software]

[News1] [News2] [Press Release]

S. Koyama, T. Omi, R. E. Kass, and S. Shinomoto,

"Information transmission using non-Poisson regular firing",

Neural Computation 25, 854 (2013). [PDF] [Journal]

T. Omi and S. Shinomoto,

"Optimizing time histograms for non-Poissonian spike trains",

Neural Computation 23, 3125 (2011). [PDF] [Journal]

S. Shinomoto, T. Omi, A. Mita, H Mushiake, K. Shima, Y. Matsuzaka, and J. Tanji,

"Deciphering elapsed time and predicting action timing from neuronal population signals", [Open Access]

Frontiers in Computational Neuroscience 5, 29 (2011). [PDF] [Journal]

T. Omi, I. Kanter, and S. Shinomoto,

"Optimal observation time window for forecasting the next earthquake",

Physical Review E 83, 026101 (2011). [PDF] [Journal]

X. Zhao, T. Omi, N. Matsuno, and S. Shinomoto,

"A non-universal aspect in the temporal occurrence of earthquakes", [Open Access]

New Journal of Physics 12, 063010 (2010). [PDF] [Journal]

T. Omi and S. Shinomoto,

"Can distributed delays perfectly stabilize dynamical networks?",

Physical Review E 77, 046214 (2008). [PDF] [Journal]

T. Omi and S. Shinomoto,

"Reverberating activity in a neural network with distributed signal transmission delays",

Physical Review E 76, 051908 (2007). [PDF] [Journal]