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Incorporating Causality with Deep Learning in Predicting Short-Term and Seasonal Sea Ice
16 Jul 2024 | Contributor(s):: Emam Hossain, Sahara Ali, Yiyi Huang, Nicole Schlegel, Jianwu Wang, Aneesh Subramanian, Md Osman Gani
Abstract: Arctic sea ice (ASI) is playing a pivotal role in keeping global warming under control. However, the recently amplified decreasing sea ice trend has become a major concern. Since satellites started monitoring the ASI in 1979, every decade the Arctic has lost 13.1% of sea ice and the...
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A Survey on Causal Discovery Methods for IID and Time Series Data
16 Jul 2024 | Contributor(s):: Uzma Hasan, Emam Hossain, Md Osman Gani
Abstract: The ability to understand causality from data is one of the major milestones of human-level intelligence. Causal Discovery (CD) algorithms can identify the cause-effect relationships among the variables of a system from related observational data with certain assumptions. Over the...
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Evaluating Machine Learning and Statistical Models for Greenland Bed Topography
15 May 2024 | Contributor(s):: Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Homayra Alam, Omar Faruque, Sikan Li, Mathieu Morlighem, Jianwu Wang
Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bed topography in Greenland using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for understanding ice sheet...
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Evaluating Machine Learning and Statistical Models for Greenland Subglacial Bed Topography
15 May 2024 | Contributor(s):: Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Homayra Alam, Omar Faruque, Sikan LI, Mathieu Morlighem, Jianwu Wang
Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bedrock topography under the Greenland ice sheet using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for...
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Development and Initial Testing of XR-Based Fence Diagrams for Polar Science
23 Apr 2024 | Contributor(s):: Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, Don Engel
Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, and Don Engel. 2023. Development and Initial Testing of XR-Based Fence Diagrams for Polar Science. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA. IEEE,...
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Metrics for the Quality and Consistency of Ice Layer Annotations
23 Apr 2024 | Contributor(s):: Naomi Tack, Bayu Adhi Tama, Atefah Jebeli, Vandana P. Janeja, Don Engel, Rebecca Williams
Naomi Tack, Bayu Adhi Tama, Atefeh Jebeli, Vandana P. Janeja, Don Engel, and Rebecca Williams. 2023. Metrics for the Quality and Consistency of Ice Layer Annotations. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA....
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Visualizing the Greenland Ice Sheet in VR using Immersive Fence Diagrams
23 Apr 2024 | Contributor(s):: Naomi Tack, Rebecca Williams, Nicholas Holschuh, Sharad Sharma, Don Engel
Naomi Tack, Rebecca Williams, Nicholas Holschuh, Sharad Sharma, and Don Engel. 2023. Visualizing the Greenland Ice Sheet in VR using Immersive Fence Diagrams. In Practice and Experience in Advanced Research Computing, ACM, Portland OR USA, 429–432. DOI:...
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Initial Development of a WebXR Platform for Ice Penetrating Radar Data, to Improve our Understanding of Polar Ice Sheets.
23 Apr 2024 | Contributor(s):: Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, Don Engel
Tack, Naomi, Holschuh, Nicholas, Sharma, Sharad, Williams, Rebecca, and Engel, Don. “Initial Development of a WebXR Platform for Ice Penetrating Radar Data, to Improve our Understanding of Polar Ice Sheets.” Poster at the AGU23 meeting, IN43B-0627, December 2023