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A general framework to increase the robustness of model-based change point detection algorithms to outliers and noise.

, , , , , and . SDM, page 162-170. SIAM, (2016)

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Online Change Detection Algorithm for Noisy Time-Series: An Application Tonear-Real Time Burned Area Mapping., , and . ICDM Workshops, page 1536-1537. IEEE Computer Society, (2015)Multiple Hypothesis Object Tracking For Unsupervised Self-Learning: An Ocean Eddy Tracking Application., , , , , , and . AAAI, page 1277-1283. AAAI Press, (2013)A Novel and Scalable Spatio-Temporal Technique for Ocean Eddy Monitoring., , , , , , and . AAAI, page 281-287. AAAI Press, (2012)A Parameter-Free Spatio-Temporal Pattern Mining Model to Catalog Global Ocean Dynamics., , , , and . ICDM, page 151-160. IEEE Computer Society, (2013)Equitable development through deep learning: The case of sub-national population density estimation., , , and . ACM DEV, page 6:1-6:10. ACM, (2016)EddyScan: A physically consistent ocean eddy monitoring application., , , , , , , and . CIDU, page 96-103. IEEE, (2012)Clustering Dynamic Spatio-Temporal Patterns in The Presence of Noise and Missing Data., , , and . IJCAI, page 2575-2581. AAAI Press, (2015)Earth Science Applications of Sensor Data., , , , , , , , , and 3 other author(s). Managing and Mining Sensor Data, Springer, (2013)A general framework to increase the robustness of model-based change point detection algorithms to outliers and noise., , , , , and . SDM, page 162-170. SIAM, (2016)