Takahiro Omi - Concepedia

Author

Takahiro Omi

The University of Tokyo

Also Known As

Omi, Takahiro, Takahiro OMI, Takahiro Omi

Publications

609

Citations

H-Index

Concepts

All Affiliations

The University of Tokyo Kyoto University The Institute of Statistical Mathematics

About

Takahiro Omi is an author at The University of Tokyo specializing in engineering, data science, and computational neuroscience.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	9	9	399
2	Business	1	1	32
3	Health Sciences	1	1	11
4	Management	1	1	92
5	Public Health	1	1	69

Takahiro Omi

Publications

587

Citations

H-Index

Page 1

	Year	Citations
Forecasting large aftershocks within one day after the main shock Takahiro Omi, Yosihiko Ogata, Yoshito Hirata, Scientific Reports	2013	130
Estimating the ETAS model from an early aftershock sequence Takahiro Omi, Yosihiko Ogata, Yoshito Hirata, Geophysical Research Letters Forecasting MethodologyEngineeringData DeficiencyComputational ModelEarthquake Scenario	2014	92
Intermediate‐term forecasting of aftershocks from an early aftershock sequence: Bayesian and ensemble forecasting approaches Takahiro Omi, Yosihiko Ogata, Yoshito Hirata, Journal of Geophysical Research Solid Earth Forecasting MethodologyBayesian StatisticsRobust ForecastingEnsemble Forecasting ApproachesEvent Understanding	2015	69
Implementation of a Real‐Time System for Automatic Aftershock Forecasting in Japan Takahiro Omi, Yosihiko Ogata, Katsuhiko Shiomi, Seismological Research Letters Forecasting MethodologyProbabilistic ForecastingEngineeringData SciencePredictive Analytics	2018	52
Fully Neural Network based Model for General Temporal Point Processes Takahiro Omi, Naonori Ueda, Kazuyuki Aihara arXiv (Cornell University) EngineeringMachine LearningData ScienceComputational NeuroscienceSequential Learning	2019	50
Automatic Aftershock Forecasting: A Test Using Real‐Time Seismicity Data in Japan Takahiro Omi, Yosihiko Ogata, Katsuhiko Shiomi, Bulletin of the Seismological Society of America Forecasting MethodologyProbability ForecastEngineeringEarthquake HazardsDisaster Detection	2016	39
Optimizing Time Histograms for Non-Poissonian Spike Trains Takahiro Omi, Shigeru Shinomoto Neural Computation	2011	37
Fully Neural Network based Model for General Temporal Point Processes Takahiro Omi, Naonori Ueda, Kazuyuki Aihara arXiv (Cornell University) EngineeringMachine LearningData ScienceComputational NeuroscienceSequential Learning	2019	33
Hawkes process model with a time-dependent background rate and its application to high-frequency financial data Takahiro Omi, Yoshito Hirata, Kazuyuki Aihara Physical review. E EngineeringHawkes Process ModelMacroeconomic ForecastingHigh-frequency Financial DataEconomic Fluctuation	2017	32
Can distributed delays perfectly stabilize dynamical networks? Takahiro Omi, Shigeru Shinomoto Physical Review E Dynamic NetworkDynamical NetworksTime Delay SystemExponential DistributionNetwork Science	2008	20

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