Ganguly, Auroop R.

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

Karpatne, A., Atluri, G., Faghmous, J. H., Steinbach, M., Banerjee, A., Ganguly, A., Shekhar, S., Samatova, N., & Kumar, V. (2017) · IEEE Transactions on Knowledge and Data Engineering

Model Reduction and Neural NetworksMachine Learning in Materials Science

Cited by 1,752

Intensification and spatial homogenization of coastal upwelling under climate change

Wang, D., Gouhier, T. C., Menge, B. A., & Ganguly, A. R. (2015) · Nature

Oceanographic and Atmospheric ProcessesClimate variability and models

Cited by 447

Sparse Group Lasso: Consistency and Climate Applications

Chatterjee, S., Steinhaeuser, K., Banerjee, A., Chatterjee, S., & Ganguly, A. (2012) · Proceedings of the 2012 SIAM International Conference on Data Mining

Statistical Methods and InferenceSpatial and Panel Data Analysis

Cited by 72

Hybrid physics-AI outperforms numerical weather prediction for extreme precipitation nowcasting

Das, P., Posch, A., Barber, N., Hicks, M., Duffy, K., Vandal, T., Singh, D., Werkhoven, K. V., & Ganguly, A. R. (2024) · npj Climate and Atmospheric Science

Meteorological Phenomena and SimulationsHydrological Forecasting Using AI

Cited by 58

Theory-Guided Data Science for Climate Change

Faghmous, J. H., Banerjee, A., Shekhar, S., Steinbach, M., Kumar, V., Ganguly, A. R., & Samatova, N. (2014) · Computer

Climate variability and modelsSpatial and Panel Data Analysis

Cited by 42

A graph‐based approach to find teleconnections in climate data

Kawale, J., Liess, S., Kumar, A., Steinbach, M., Snyder, P., Kumar, V., Ganguly, A. R., Samatova, N. F., & Semazzi, F. (2013) · Statistical Analysis and Data Mining: The ASA Data Science Journal

Climate variability and modelsEcosystem dynamics and resilience

Cited by 37