no code implementations • 30 May 2025 • Zahid Hassan Tushar, Adeleke Ademakinwa, Jianwu Wang, Zhibo Zhang, Sanjay Purushotham
Satellite radiance measurements enable global COT retrieval, but challenges like 3D cloud effects, viewing angles, and atmospheric interference must be addressed to ensure accurate estimation.
1 code implementation • 29 May 2025 • Bayu Adhi Tama, Mansa Krishna, Homayra Alam, Mostafa Cham, Omar Faruque, Gong Cheng, Jianwu Wang, Mathieu Morlighem, Vandana Janeja
Understanding Greenland's subglacial topography is critical for projecting the future mass loss of the ice sheet and its contribution to global sea-level rise.
no code implementations • 20 May 2025 • Haishi Bai, Jozo Dujmovic, Jianwu Wang
As machine learning models and autonomous agents are increasingly deployed in high-stakes, real-world domains such as healthcare, security, finance, and robotics, the need for transparent and trustworthy explanations has become critical.
1 code implementation • 8 May 2025 • Seraj Al Mahmud Mostafa, Chenxi Wang, Jia Yue, Yuta Hozumi, Jianwu Wang
Object localization in satellite imagery is particularly challenging due to the high variability of objects, low spatial resolution, and interference from noise and dominant features such as clouds and city lights.
no code implementations • 4 Apr 2025 • Zahid Hassan Tushar, Adeleke Ademakinwa, Jianwu Wang, Zhibo Zhang, Sanjay Purushotham
Accurate cloud property retrieval is vital for understanding cloud behavior and its impact on climate, including applications in weather forecasting, climate modeling, and estimating Earth's radiation balance.
no code implementations • 8 Mar 2025 • Md Azim Khan, Aryya Gangopadhyay, Jianwu Wang, Robert F. Erbacher
Situational awareness applications rely heavily on real-time processing of visual and textual data to provide actionable insights.
no code implementations • 3 Mar 2025 • Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova, Wahid Bhimji, Wei-Lun Chao, Chris Harris, Shih-Chieh Hsu, Hilmar Lapp, Mark S. Neubauer, Josephine Namayanja, Aneesh Subramanian, Philip Harris, Advaith Anand, David E. Carlyn, Subhankar Ghosh, Christopher Lawrence, Eric 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 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 Duarte, Isla Duporge, Urbas Ekka, Saba Entezari Heravi, Hao Fang, Rian Flynn, Geoffrey Fox, Emily Freed, Hang Gao, Jing Gao, Julia Gonski, Matthew Graham, Abolfazl Hashemi, Scott Hauck, James Hazelden, Joshua Henry Peterson, Duc Hoang, Wei Hu, Mirco Huennefeld, David Hyde, Vandana 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, Min Namgung, Andrzej Novak, Andrew Novick, Amy Orsborn, Anand Padmanabhan, Jia-Cheng Pan, Sneh Pandya, Zhiyuan Pei, Ana Peixoto, George Percivall, Alex Po Leung, Sanjay Purushotham, Zhiqiang Que, Melissa Quinnan, Arghya Ranjan, Dylan Rankin, Christina Reissel, Benedikt Riedel, Dan Rubenstein, Argyro Sasli, Eli Shlizerman, Arushi Singh, Kim Singh, Eric R. Sokol, Arturo Sorensen, Yu Su, Mitra Taheri, Vaibhav Thakkar, Ann Mariam Thomas, Eric Toberer, Chenghan Tsai, Rebecca Vandewalle, Arjun Verma, Ricco C. Venterea, He Wang, Jianwu Wang, Sam Wang, Shaowen Wang, Gordon Watts, Jason Weitz, Andrew Wildridge, Rebecca Williams, Scott Wolf, Yue Xu, Jianqi Yan, Jai Yu, Yulei Zhang, Haoran Zhao, Ying Zhao, Yibo Zhong
We present the different datasets along with a scheme to make machine learning challenges around the three datasets findable, accessible, interoperable, and reusable (FAIR).
no code implementations • 19 Sep 2024 • Francis Ndikum Nji, Omar Faruque, Mostafa Cham, Janeja Vandana, Jianwu Wang
Classifying subsets based on spatial and temporal features is crucial to the analysis of spatiotemporal data given the inherent spatial and temporal variability.
no code implementations • 9 Sep 2024 • Zahra Khanjani, Tolulope Ale, Jianwu Wang, Lavon Davis, Christine Mallinson, Vandana P. Janeja
Several types of spoofed audio, such as mimicry, replay attacks, and deepfakes, have created societal challenges to information integrity.
1 code implementation • 26 Aug 2024 • Seraj Al Mahmud Mostafa, Omar Faruque, Chenxi Wang, Jia Yue, Sanjay Purushotham, Jianwu Wang
Atmospheric gravity waves occur in the Earths atmosphere caused by an interplay between gravity and buoyancy forces.
no code implementations • 13 May 2024 • Sahara Ali, Omar Faruque, Jianwu Wang
We then propose our deep learning based potential outcome model for spatiotemporal causal inference.
no code implementations • 10 Apr 2024 • Seraj Al Mahmud Mostafa, Jinbo Wang, Benjamin Holt, Jianwu Wang
Ocean eddies play a significant role both on the sea surface and beneath it, contributing to the sustainability of marine life dependent on oceanic behaviors.
no code implementations • 3 Apr 2024 • Sahara Ali, Uzma Hasan, Xingyan Li, Omar Faruque, Akila Sampath, Yiyi Huang, Md Osman Gani, Jianwu Wang
This survey paper covers the breadth and depth of time-series and spatiotemporal causality methods, and their applications in Earth Science.
no code implementations • 1 Apr 2024 • Omar Faruque, Sahara Ali, Xue Zheng, Jianwu Wang
The growing availability and importance of time series data across various domains, including environmental science, epidemiology, and economics, has led to an increasing need for time-series causal discovery methods that can identify the intricate relationships in the non-stationary, non-linear, and often noisy real world data.
1 code implementation • 29 Jan 2024 • Xingyan Li, Andrew M. Sayer, Ian T. Carroll, Xin Huang, Jianwu Wang
In response, this paper introduces MT-HCCAR, an end-to-end deep learning model employing multi-task learning to simultaneously tackle cloud masking, cloud phase retrieval (classification tasks), and COT prediction (a regression task).
no code implementations • 10 Aug 2023 • Weilong Ding, Tianpu Zhang, Jianwu Wang, Zhuofeng Zhao
In our method, data normalization strategy is used to deal with data imbalance, due to long-tail distribution of traffic flow at network-wide toll stations.
1 code implementation • 8 Aug 2023 • Sahara Ali, Jianwu Wang
Arctic amplification has altered the climate patterns both regionally and globally, resulting in more frequent and more intense extreme weather events in the past few decades.
1 code implementation • 27 Apr 2023 • Omar Faruque, Francis Ndikum Nji, Mostafa Cham, Rohan Mandar Salvi, Xue Zheng, Jianwu Wang
Concentrating on joint deep representation learning of spatial and temporal features, we propose Deep Spatiotemporal Clustering (DSC), a novel algorithm for the temporal clustering of high-dimensional spatiotemporal data using an unsupervised deep learning method.
no code implementations • 22 Feb 2023 • Sahara Ali, Omar Faruque, Yiyi Huang, Md. Osman Gani, Aneesh Subramanian, Nicole-Jienne Shchlegel, Jianwu Wang
Through experiments on synthetic and observational data, we show how our research can substantially improve the ability to quantify leading causes of Arctic sea ice melt, further paving paths for causal inference in observational Earth science.
no code implementations • 10 May 2022 • Xin Wang, Azim Khan, Jianwu Wang, Aryya Gangopadhyay, Carl E. Busart, Jade Freeman
In this paper, we study how to best leverage edge and cloud resources to achieve better accuracy and latency for stream analytics using a type of RNN model called long short-term memory (LSTM).
1 code implementation • 17 Dec 2021 • Xin Wang, Pei Guo, Xingyan Li, Aryya Gangopadhyay, Carl E. Busart, Jade Freeman, Jianwu Wang
To tackle these problems, we leverage serverless computing and containerization techniques for automated scalable execution and reproducibility, and utilize the adapter design pattern to enable application portability and reproducibility across different clouds.
1 code implementation • 27 Jul 2021 • Sahara Ali, Yiyi Huang, Xin Huang, Jianwu Wang
Accurately forecasting Arctic sea ice from subseasonal to seasonal scales has been a major scientific effort with fundamental challenges at play.
no code implementations • 24 Dec 2020 • Pei Guo, Achuna Ofonedu, Jianwu Wang
Causality discovery mines cause-effect relationships among different variables of a system and has been widely used in many disciplines including climatology and neuroscience.
no code implementations • 24 Aug 2018 • Wenbin Zhang, Jianwu Wang, Daeho Jin, Lazaros Oreopoulos, Zhibo Zhang
A self-organizing map (SOM) is a type of competitive artificial neural network, which projects the high-dimensional input space of the training samples into a low-dimensional space with the topology relations preserved.