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Nader Shakibay Senobari
Nader Shakibay Senobari
Assistant Project Scientist, UC Riverside, Computer Science Department
Verified email at ucr.edu
Title
Cited by
Cited by
Year
Matrix profile ii: Exploiting a novel algorithm and gpus to break the one hundred million barrier for time series motifs and joins
Y Zhu, Z Zimmerman, N Shakibay Senobari, CCM Yeh, G Funning, ...
2016 IEEE 16th international conference on data mining (ICDM), 739-748, 2016
2742016
Matrix Profile XIV: Scaling Time Series Motif Discovery with GPUs to Break a Quintillion Pairwise Comparisons a Day and Beyond
Z Zimmerman, K Kamgar, N Shakibay Senobari, B Crites, G Funning, ...
Proceedings of the ACM Symposium on Cloud Computing, 74-86, 2019
702019
Matrix profile xx: Finding and visualizing time series motifs of all lengths using the matrix profile
F Madrid, S Imani, R Mercer, Z Zimmerman, N Shakibay Senobari, ...
2019 IEEE International Conference on Big Knowledge (ICBK), 175-182, 2019
542019
Super‐Efficient Cross‐Correlation (SEC‐C): A Fast Matched Filtering Code Suitable for Desktop Computers
N Shakibay Senobari, GJ Funning, E Keogh, Y Zhu, CCM Yeh, ...
Seismological Research Letters 90 (1), 322-334, 2019
452019
Exploiting a novel algorithm and GPUs to break the ten quadrillion pairwise comparisons barrier for time series motifs and joins
Y Zhu, Z Zimmerman, N Shakibay Senobari, CCM Yeh, G Funning, ...
Knowledge and Information Systems 54 (1), 203-236, 2018
412018
The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code
Y Zhu, S Gharghabi, DF Silva, HA Dau, CCM Yeh, N Shakibay Senobari, ...
Data Mining and Knowledge Discovery 34 (4), 949-979, 2020
332020
Widespread fault creep in the northern San Francisco Bay Area revealed by multistation cluster detection of repeating earthquakes
N Shakibay Senobari, GJ Funning
Geophysical Research Letters 46 (12), 6425-6434, 2019
202019
Matrix profile xviii: Time series mining in the face of fast moving streams using a learned approximate matrix profile
Z Zimmerman, N Shakibay Senobari, G Funning, E Papalexakis, S Oymak, ...
2019 IEEE International Conference on Data Mining (ICDM), 936-945, 2019
192019
Using the similarity Matrix Profile to investigate foreshock behavior of the 2004 Parkfield earthquake
N Shakibay Senobari, G Funning, Z Zimmerman, Y Zhu, E Keogh
AGU Fall Meeting 2018, 2018
82018
Scaling Time Series Motif Discovery with GPUs: Breaking the Quintillion Pairwise Comparisons a Day Barrier
Z Zimmerman, K Kamgar, Y Zhu, N Shakibay Senobari, B Crites, ...
Preprint],[Online]. Available at: https://www. cs. ucr. edu/% 7Eeamonn …, 2018
82018
A Python Code for Detecting True Repeating Earthquakes from Self‐Similar Waveforms (FINDRES)
M Sugan, S Campanella, A Vuan, N Shakibay Senobari
Seismological Society of America 93 (5), 2847-2857, 2022
22022
Introducing the contrast profile: a novel time series primitive that allows real world classification
R Mercer, S Alaee, A Abdoli, NS Senobari, S Singh, A Murillo, E Keogh
Data Mining and Knowledge Discovery 36 (2), 877-915, 2022
22022
Distribution of creep in the northern San Francisco Bay Area illuminated by repeating earthquakes and InSAR
G Funning, N Shakibay Senobari, JL Swiatlowski
AGU Fall Meeting Abstracts 2017, T21A-0542, 2017
22017
The matrix profile: a fast and sensitive template matching method for seismic event detection that does not require templates
NS Senobari, G Funning, Z Zimmermann, Y Zhu, PM Shearer, P Brisk, ...
Authorea Preprints, 2022
2022
The matrix profile: a fast and sensitive template matching method for seismic event detection that does not require templates
N Shakibay Senobari, G Funning, Z Zimmermann, Y Zhu, PM Shearer, ...
ESS Open Archive eprints 105, essoar. 10512525, 2022
2022
Sulaimaniyah 2015 Earthquake Swarm Analysis Using Matrix Profile TechniqueI
GI Aleqabi, ME Wysession, N Shakibay Senobari, E Keogh, Z Zimmerman, ...
AGU Fall Meeting Abstracts 2020, S020-0010, 2020
2020
Using the similarity Matrix Profile to detect and study foreshocks and aftershocks of the 2019 Ridgecrest sequence
N Shakibay Senobari, G Funning, Z Zimmerman, PM Shearer, P Brisk, ...
AGU Fall Meeting 2019, 2019
2019
Combining Seismology and Geodesy to Better Constrain Earthquake Source Parameters and Shallow Fault Behavior
N Shakibay Senobari
University of California, Riverside, 2019
2019
The Similarity Matrix Profile, an efficient method for detecting seismic events in very long time series
G Funning, N Shakibay Senobari, Z Zimmerman, Y Zhu, E Keogh
AGU Fall Meeting 2018, 2018
2018
The Similarity Matrix Profile, an efficient method for detecting seismic events in very long time series
N Shakibay Senobari, G Funning, Z Zimmerman, Y Zhu, E Keogh
AGU Fall Meeting Abstracts 2018, S33B-05, 2018
2018
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