Aneesh Subramanian

According to our database, Aneesh Subramanian authored at least 12 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Building Machine Learning Challenges for Anomaly Detection in Science.

Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova, Wahid Bhimji, Wei-Lun Chao, Chris Harris, Shih-Chieh Hsu, Hilmar Lapp, Mark S. Neubauer, Josephine M. Namayanja, Aneesh Subramanian, Philip C. Harris, Advaith Anand, David Edward Carlyn, Subhankar Ghosh, Christopher G. Lawrence, Eric A. Moreno, Ryan Raikman, Jiaman Wu, Ziheng Zhang, Bayu Adhi, Mohammad Ahmadi Gharehtoragh, Saúl Alonso-Monsalve, Marta Babicz, Furqan Baig, Namrata Banerji, William Bardon, Tyler Barna, Tanya Y. Berger-Wolf, Adji Bousso Dieng, Micah Brachman, Quentin Buat, David C. Y. Hui, Phuong Cao, Franco Cerino, Yi-Chun Chang, Shivaji Chaulagain, An-Kai Chen, Deming Chen, Eric Chen, Chia-Jui Chou, Zih-Chen Ciou, Miles Cochran-Branson, Artur Cordeiro Oudot Choi, Michael Coughlin, Matteo Cremonesi, Maria Dadarlat, Peter Darch, Malina Desai, Daniel Diaz, Steven Dillmann, Javier M. Duarte, Isla Duporge, Urbas Ekka, Saba Entezari Heravi, Hao Fang, Rian Flynn, Geoffrey Fox, Emily Freed, Hang Gao, Jing Gao, Julia Gonski, Matthew J. Graham, Abolfazl Hashemi, Scott Hauck, James Hazelden, Joshua Henry Peterson, Duc Hoang, Wei Hu, Mirco Hünnefeld, David Hyde, Vandana P. Janeja, Nattapon Jaroenchai, Haoyi Jia, Yunfan Kang, Maksim Kholiavchenko, Elham E Khoda, Sangin Kim, Aditya Kumar, Bo-Cheng Lai, Trung Le, Chi-Wei Lee, JangHyeon Lee, Shaocheng Lee, Suzan van der Lee, Charles Lewis, Haitong Li, Haoyang Li, Henry Liao, Mia Liu, Xiaolin Liu, Xiulong Liu, Vladimir Loncar, Fangzheng Lyu, Ilya Makarov, Abhishikth Mallampalli Chen-Yu Mao, Alexander Michels, Alexander Migala, Farouk Mokhtar, Mathieu Morlighem

CoRR, March, 2025

Engaging K-12 Learners in Data Annotation for AI Climate Models.

Michael MacFerrin, Edward Boyda, Kimberly Young, Josephine M. Namayanja, Aneesh Subramanian, Mohamed F. Mokbel, Lujie Karen Chen, Vandana P. Janeja

Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 2, 2025

Correlation to Causation: A Causal Deep Learning Framework for Arctic Sea Ice Prediction.

Emam Hossain, Muhammad Hasan Ferdous, Jianwu Wang, Aneesh Subramanian, Md. Osman Gani

Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, 2025

Causal Time Series Modeling of Supraglacial Lake Evolution in Greenland under Distribution Shift.

Emam Hossain, Muhammad Hasan Ferdous, Devon Dunmire, Aneesh Subramanian, Md. Osman Gani

Proceedings of the International Conference on Machine Learning and Applications, 2025

2024

Towards Kriging-informed Conditional Diffusion for Regional Sea-Level Data Downscaling.

Subhankar Ghosh, Arun Sharma, Jayant Gupta, Aneesh Subramanian, Shashi Shekhar

CoRR, 2024

Time Series Classification of Supraglacial Lakes Evolution over Greenland Ice Sheet.

Emam Hossain, Md. Osman Gani, Devon Dunmire, Aneesh Subramanian, Hammad Younas

CoRR, 2024

Towards Kriging-informed Conditional Diffusion for Regional Sea-Level Data Downscaling: A Summary of Results.

Subhankar Ghosh, Arun Sharma, Jayant Gupta, Aneesh Subramanian, Shashi Shekhar

Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024

2023

Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-variability-aware Approach.

Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

CoRR, 2023

STint: Self-supervised Temporal Interpolation for Geospatial Data.

Nidhin Harilal, Bri-Mathias S. Hodge, Aneesh Subramanian, Claire Monteleoni

CoRR, 2023

Quantifying Causes of Arctic Amplification via Deep Learning Based Time-Series Causal Inference.

Sahara Ali, Omar Faruque, Yiyi Huang, Md. Osman Gani, Aneesh Subramanian, Nicole-Jeanne Schlegel, Jianwu Wang

Proceedings of the International Conference on Machine Learning and Applications, 2023

2018

Statistical Characteristics of Long-Term High-Resolution Precipitable Water Vapor Data at Darwin.

Kimberly Leung, Aneesh Subramanian, Samuel S. P. Shen

Adv. Data Sci. Adapt. Anal., 2018

2016

Simulation of High-Resolution Precipitable Water Data by a Stochastic Model with a Random Trigger.

Kimberly Leung, Max Velado, Aneesh Subramanian, Guang J. Zhang, Richard C. J. Somerville, Samuel S. P. Shen

Adv. Data Sci. Adapt. Anal., 2016