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ORCIDSreelekha Guggilam
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2020 – today
- 2025
[j3]Ruhaan Singh
, Sreelekha Guggilam:
Iterative Misclassification Error Training (IMET): An Optimized Neural Network Training Technique for Image Classification. IEEE Access 13: 178148-178159 (2025)- [i5]Ruhaan Singh, Sreelekha Guggilam:
Iterative Misclassification Error Training (IMET): An Optimized Neural Network Training Technique for Image Classification. CoRR abs/2507.02979 (2025) - [i4]Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang:
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR abs/2509.02661 (2025) - 2023
- [j2]Sreelekha Guggilam, Varun Chandola, Abani K. Patra:
Large Deviations Anomaly Detection (LAD) for collection of multivariate time series data: Applications to COVID-19 data. J. Comput. Sci. 72: 102101 (2023) - [c4]Philipe A. Dias, Abhishek Potnis, Sreelekha Guggilam, Lexie Yang, Aristeidis Tsaris, Henry Medeiros, Dalton D. Lunga:
An Agenda for Multimodal Foundation Models for Earth Observation. IGARSS 2023: 1237-1240 - [i3]Sreelekha Guggilam, Varun Chandola, Abani K. Patra:
Large Deviations for Accelerating Neural Networks Training. CoRR abs/2303.00954 (2023) - 2022
- [j1]Sreelekha Guggilam, Varun Chandola, Abani K. Patra:
Tracking clusters and anomalies in evolving data streams. Stat. Anal. Data Min. 15(2): 156-178 (2022) - [c3]Sreelekha Guggilam, Varun Chandola, Abani K. Patra:
Classifying Anomalous Members in a Collection of Multivariate Time Series Data Using Large Deviations Principle: An Application to COVID-19 Data. ICCS (1) 2022: 133-149 - [c2]Snehalkumar (Neil) S. Gaikwad, Shankar Iyer, Dalton D. Lunga, Takahiro Yabe, Xiaofan Liang, Bhavani Ananthabhotla, Nikhil Behari, Sreelekha Guggilam, Guanghua Chi:
Data-driven Humanitarian Mapping and Policymaking: Toward Planetary-Scale Resilience, Equity, and Sustainability. KDD 2022: 4872-4873 - 2021
- [i2]Sreelekha Guggilam, Varun Chandola, Abani K. Patra:
Anomaly Detection for High-Dimensional Data Using Large Deviations Principle. CoRR abs/2109.13698 (2021)
2010 – 2019
- 2019
- [c1]Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra:
Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data. ICCS (4) 2019: 45-59 - [i1]Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra:
Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised). CoRR abs/1911.00184 (2019)
Coauthor Index
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