Sreelekha Guggilam

12 papers A* 1C 1Journal 8Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Iterative Misclassification Error Training (IMET): An Optimized Neural Network Training Technique for Image Classification. IEEE Access Ruhaan Singh, Sreelekha Guggilam
2025	J	`jnl`	Iterative Misclassification Error Training (IMET): An Optimized Neural Network Training Technique for Image Classification. CoRR Ruhaan Singh, Sreelekha Guggilam
2025	J	`jnl`	The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR 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
2023	C	`conf`	An Agenda for Multimodal Foundation Models for Earth Observation. IGARSS Philipe A. Dias, Abhishek Potnis, Sreelekha Guggilam, Lexie Yang, Aristeidis Tsaris, Henry Medeiros, Dalton D. Lunga
2023	J	`jnl`	Large Deviations Anomaly Detection (LAD) for collection of multivariate time series data: Applications to COVID-19 data. J. Comput. Sci. Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2023	J	`jnl`	Large Deviations for Accelerating Neural Networks Training. CoRR Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2022	—	`conf`	Classifying Anomalous Members in a Collection of Multivariate Time Series Data Using Large Deviations Principle: An Application to COVID-19 Data. ICCS (1) Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2022	A*	`conf`	Data-driven Humanitarian Mapping and Policymaking: Toward Planetary-Scale Resilience, Equity, and Sustainability. KDD Snehalkumar (Neil) S. Gaikwad, Shankar Iyer, Dalton D. Lunga, Takahiro Yabe, Xiaofan Liang, Bhavani Ananthabhotla, Nikhil Behari, Sreelekha Guggilam, Guanghua Chi
2022	J	`jnl`	Tracking clusters and anomalies in evolving data streams. Stat. Anal. Data Min. Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2021	J	`jnl`	Anomaly Detection for High-Dimensional Data Using Large Deviations Principle. CoRR Sreelekha Guggilam, Varun Chandola, Abani K. Patra
2019	J	`jnl`	Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised). CoRR Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra
2019	—	`conf`	Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data. ICCS (4) Sreelekha Guggilam, Syed Mohammed Arshad Zaidi, Varun Chandola, Abani K. Patra