James H. Faghmous

发表

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

Vipin Kumar, Snigdhansu Chatterjee, Xi C. Chen, 2016, SDM.

Multiple Hypothesis Object Tracking For Unsupervised Self-Learning: An Ocean Eddy Tracking Application

Vipin Kumar, James H. Faghmous, Shyam Boriah, 2013, AAAI.

Global Monitoring of Inland Water Dynamics: State-of-the-Art, Challenges, and Opportunities

Xi Chen, Anuj Karpatne, Vipin Kumar, 2016, Computational Sustainability.

Computing and Climate

Shashi Shekhar, Vipin Kumar, James H. Faghmous, 2015, Comput. Sci. Eng..

Unsupervised Method for Water Surface Extent Monitoring Using Remote Sensing Data

Vipin Kumar, Xi C. Chen, Sichao Shi, 2015 .

A Parameter-Free Spatio-Temporal Pattern Mining Model to Catalog Global Ocean Dynamics

Vipin Kumar, Snigdhansu Chatterjee, James H. Faghmous, 2013, 2013 IEEE 13th International Conference on Data Mining.

Online Change Detection Algorithm for Noisy Time-Series: An Application Tonear-Real Time Burned Area Mapping

Vipin Kumar, Xi C. Chen, James H. Faghmous, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

EddyScan: A physically consistent ocean eddy monitoring application

Vipin Kumar, James H. Faghmous, Shyam Boriah, 2012, 2012 Conference on Intelligent Data Understanding.

Spatio-Temporal Consistency as a Means to Identify Unlabeled Objects in a Continuous Data Field

Vipin Kumar, James H. Faghmous, Hung Nguyen, 2014, AAAI.

A Guide to Climate Datasets: Summary and Research Challenges

Anuj Karpatne, James H. Faghmous, Vipin Kumar, 2015 .

Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

Nagiza F. Samatova, Shashi Shekhar, Anuj Karpatne, 2016, IEEE Transactions on Knowledge and Data Engineering.

Earth Science Applications of Sensor Data

Anuj Karpatne, Vipin Kumar, Michael S. Steinbach, 2013, Managing and Mining Sensor Data.

Equitable development through deep learning: The case of sub-national population density estimation

James H. Faghmous, Patrick Doupe, Emilie Bruzelius, 2016, ACM DEV.

Spatio-Temporal Data Mining for Scalable Ocean Eddy Monitoring

James H. Faghmous, Stefan Liess, V. Kumar, 2012 .

Clustering Dynamic Spatio-Temporal Patterns in The Presence of Noise and Missing Data

Vipin Kumar, Xi C. Chen, James H. Faghmous, 2015, IJCAI.

Theory-Guided Data Science for Climate Change

Nagiza F. Samatova, Shashi Shekhar, Vipin Kumar, 2014, Computer.

A Novel and Scalable Spatio-Temporal Technique for Ocean Eddy Monitoring

Vipin Kumar, James H. Faghmous, Shyam Boriah, 2012, AAAI.

A daily global mesoscale ocean eddy dataset from satellite altimetry

James H. Faghmous, Vipin Kumar, I. Frenger, 2015, Scientific Data.

Toward enhanced understanding and projections of climate extremes using physics-guided data mining techniques

Wei-keng Liao, James H. Faghmous, Ankit Agrawal, 2014 .

Spatio-temporal Data Mining for Climate Data: Advances, Challenges, and Opportunities

James H. Faghmous, Vipin Kumar, Vipin Kumar, 2014 .

disParities: a structured tutoriaL

James H. Faghmous, S. Basu, P. Doupe, 2020 .

TR 12-012 Understanding the Sea SurfaceTemperature-Tropical Cyclone Relationship : A Data Driven Approach

James H. Faghmous, A. Ganguly, S. Liess, 2012 .

Understanding the sea surface temperature - Tropical cyclone relationship: A data-driven approach

James H. Faghmous, M. Steinbach, A. Ganguly, 2011, CIDU 2011.

CHANGE POINT DETECTION FOR REMOTE SENSING TIME SERIES

Xi C. Chen, James H. Faghmous, Vipin Kumar, 2015 .

Machine Learning for Health Services Researchers.

James H. Faghmous, Sanjay Basu, Patrick Doupe, 2019, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

A Big Data Guide to Understanding Climate Change: The Case for Theory-Guided Data Science

James H. Faghmous, James H Faghmous, Vipin Kumar, 2014, Big Data.

Assessment of Risk of Harm Associated With Intensive Blood Pressure Management Among Patients With Hypertension Who Smoke

James H. Faghmous, P. Doupe, Aaron Baum, 2019, JAMA network open.

Targeting weight loss interventions to reduce cardiovascular complications of type 2 diabetes: a machine learning-based post-hoc analysis of heterogeneous treatment effects in the Look AHEAD trial.

James H. Faghmous, S. Basu, R. Tamler, 2017, The lancet. Diabetes & endocrinology.

Huntington's disease in the United States: Variation by demographic and socioeconomic factors

James H. Faghmous, S. Basu, Aaron Baum, 2019, Movement disorders : official journal of the Movement Disorder Society.

Machine Learning Methods for Precision Medicine Research Designed to Reduce Health Disparities: A Structured Tutorial.

James H. Faghmous, James H Faghmous, Sanjay Basu, 2020, Ethnicity & disease.