Probabilistic Inverse Modeling: An Application in Hydrology - Somya Sharma; Rahul Ghosh; Arvind Renganathan; Xiang Li; Snigdhansu Chatterjee; John Nieber; Christopher J. Duffy; Vipin Kumar (Proceedings of the 2023 SIAM International Conference on Data Mining, SDM 2023, Minneapolis-St. Paul Twin Cities, MN, USA, April 27-29, 2023, 2023)

Uncertainty Quantification in Inverse Models in Hydrology - Somya Sharma Chatterjee; Rahul Ghosh; Arvind Renganathan; Xiang Li; Snigdhansu Chatterjee; John Nieber; Christopher J. Duffy; Vipin Kumar (CoRR, 2023)

Machine Learning Methods for Multiscale Physics and Urban Engineering Problems - Somya Sharma; Marten Thompson; Debra F. Laefer; Michael Lawler; Kevin L. McIlhany; Olivier Pauluis; Dallas R. Trinkle; Snigdhansu Chatterjee (Entropy, 2022)

On weighted multivariate sign functions - Subhabrata Majumdar; Snigdhansu Chatterjee (J. Multivar. Anal., 2022)

Feature selection using e-values - Subhabrata Majumdar; Snigdhansu Chatterjee (International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA, 2022)

Feature Selection using e-values - Subhabrata Majumdar; Snigdhansu Chatterjee (CoRR, 2022)

Probabilistic Inverse Modeling: An Application in Hydrology - Somya Sharma; Rahul Ghosh; Arvind Renganathan; Xiang Li; Snigdhansu Chatterjee; John Nieber; Christopher J. Duffy; Vipin Kumar (CoRR, 2022)

Winsorization for Robust Bayesian Neural Networks - Somya Sharma; Snigdhansu Chatterjee (Entropy, 2021)

Generalized Multivariate Signs for Nonparametric Hypothesis Testing in High Dimensions - Subhabrata Majumdar; Snigdhansu Chatterjee (CoRR, 2021)

Approximate Bayesian Computation for Physical Inverse Modeling - Neel Chatterjee; Somya Sharma; Sarah L. Swisher; Snigdhansu Chatterjee (CoRR, 2021)

Semiparametric modeling of time-varying activation and connectivity in task-based fMRI data - Jun Young Park; Jörg Polzehl; Snigdhansu Chatterjee; André Brechmann; Mark Fiecas (Comput. Stat. Data Anal., 2020)

Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks - Saurabh Agrawal; Michael S. Steinbach; Daniel Boley; Snigdhansu Chatterjee; Gowtham Atluri; Anh The Dang; Stefan Liess; Vipin Kumar (IEEE Trans. Knowl. Data Eng., 2020)

A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series - Saurabh Agrawal; Saurabh Verma; Anuj Karpatne; Stefan Liess; Snigdhansu Chatterjee; Vipin Kumar (CoRR, 2019)

Mining Sub-Interval Relationships In Time Series Data - Saurabh Agrawal; Saurabh Verma; Gowtham Atluri; Anuj Karpatne; Stefan Liess; Angus W. MacDonald III; Snigdhansu Chatterjee; Vipin Kumar (CoRR, 2018)

Mining Novel Multivariate Relationships in Time Series Data Using Correlation Networks - Saurabh Agrawal; Michael S. Steinbach; Daniel Boley; Snigdhansu Chatterjee; Gowtham Atluri; Anh The Dang; Stefan Liess; Vipin Kumar (CoRR, 2018)

Tripoles: A New Class of Relationships in Time Series Data - Saurabh Agrawal; Gowtham Atluri; Anuj Karpatne; William Haltom; Stefan Liess; Snigdhansu Chatterjee; Vipin Kumar (Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13 - 17, 2017, 2017)

A general framework to increase the robustness of model-based change point detection algorithms to outliers and noise - Xi C. Chen; Yuanshun Yao; Sichao Shi; Snigdhansu Chatterjee; Vipin Kumar; James H. Faghmous (Proceedings of the 2016 SIAM International Conference on Data Mining, Miami, Florida, USA, May 5-7, 2016, 2016)

Fast and Robust Supervised Learning in High Dimensions Using the Geometry of the Data - Ujjal Kumar Mukherjee; Subhabrata Majumdar; Snigdhansu Chatterjee (Advances in Data Mining: Applications and Theoretical Aspects - 15th Industrial Conference, ICDM 2015, Hamburg, Germany, July 11-24, 2015, Proceedings, 2015)

Fast algorithm for computing weighted projection quantiles and data depth for high-dimensional large data clouds - Ujjal Kumar Mukherjee; Snigdhansu Chatterjee (2014 IEEE International Conference on Big Data (IEEE BigData 2014), Washington, DC, USA, October 27-30, 2014, 2014)

A Parameter-Free Spatio-Temporal Pattern Mining Model to Catalog Global Ocean Dynamics - James H. Faghmous; Matthew Le; Muhammed Uluyol; Vipin Kumar; Snigdhansu Chatterjee (2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013, 2013)

Contextual Time Series Change Detection - Xi C. Chen; Karsten Steinhaeuser; Shyam Boriah; Snigdhansu Chatterjee; Vipin Kumar (Proceedings of the 13th SIAM International Conference on Data Mining, May 2-4, 2013. Austin, Texas, USA, 2013)

Spatially penalized regression for dependence analysis of rare events: A study in precipitation extremes - Debasish Das; Auroop R. Ganguly; Snigdhansu Chatterjee; Vipin Kumar; Zoran Obradovic (2012 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012, Munich, Germany, July 22-27, 2012, 2012)

Testing the significance of spatio-temporal teleconnection patterns - Jaya Kawale; Snigdhansu Chatterjee; Dominick Ormsby; Karsten Steinhaeuser; Stefan Liess; Vipin Kumar (The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '12, Beijing, China, August 12-16, 2012, 2012)

Sparse Group Lasso: Consistency and Climate Applications - Soumyadeep Chatterjee; Karsten Steinhaeuser; Arindam Banerjee; Snigdhansu Chatterjee; Auroop R. Ganguly (Proceedings of the Twelfth SIAM International Conference on Data Mining, Anaheim, California, USA, April 26-28, 2012, 2012)

High dimensional data analysis using multivariate generalized spatial quantiles - Nitai D. Mukhopadhyay; Snigdhansu Chatterjee (J. Multivar. Anal., 2011)

Anomaly Construction in Climate Data: Issues and Challenges - Jaya Kawale; Snigdhansu Chatterjee; Arjun Kumar; Stefan Liess; Michael S. Steinbach; Vipin Kumar (Proceedings of the 2011 Conference on Intelligent Data Understanding, CIDU 2011, October 19-21, 2011, Mountain View, California, USA, 2011)

Sparse Group Lasso for Regression on Land Climate Variables - Soumyadeep Chatterjee; Arindam Banerjee; Snigdhansu Chatterjee; Auroop R. Ganguly (Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on, Vancouver, BC, Canada, December 11, 2011, 2011)

Probabilistic Matrix Addition - Amrudin Agovic; Arindam Banerjee; Snigdhansu Chatterjee (Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, June 28 - July 2, 2011, 2011)

Reply to "Comment on causality and pathway search in microarray time series experiment" - Nitai D. Mukhopadhyay; Snigdhansu Chatterjee (Bioinform., 2008)

Structural Equation Modeling, A Bayesian Approach - Snigdhansu Chatterjee (Technometrics, 2008)

Causality and pathway search in microarray time series experiment - Nitai D. Mukhopadhyay; Snigdhansu Chatterjee (Bioinform., 2007)

Procrustes Problems - Snigdhansu Chatterjee (Technometrics, 2005)

Order Statistics - Snigdhansu Chatterjee (Technometrics, 2004)