(* denotes equal contribution)
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CoDiCast: Conditional Diffusion Model for Weather Prediction with Uncertainty Quantification.
Jimeng Shi, Bowen Jin, Jiawei Han, Giri Narasimhan.
(Under review)
[PDF]
[Code]
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ReFine: Boosting Time Series Prediction of Extreme Events by Reweighting and Fine-tuning.
Jimeng Shi, Azam Shirali, Giri Narasimhan.
2024 IEEE International Conference on Big Data (To appear)
[PDF]
[Code]
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TimeX++: Learning Time-Series Explanations with Information Bottleneck.
Zichuan Liu, Tianchun Wang, Jimeng Shi, Xu Zheng, Zhuomin Chen, Lei Song, Wenqian Dong, Jayantha Obeysekera, Farhad Shirani, Dongsheng Luo.
International Conference on Machine Learning (ICML) (Poster).
[PDF]
[Code]
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Physics-Informed Neural Network Approach for Solving the One-Dimensional Unsteady Shallow-Water Equations in Riverine Systems.
Zeda Yin, Jimeng Shi, Linlong Bian, William Campbell, Sumit Zanje, Arturo Leon.
Journal of Hydraulic Engineering.
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A Comprehensive Survey of Scoring Functions for Protein Docking Models.
Azam Shirali, Vitalii Stebliankin, Jimeng Shi, Giri Narasimhan.
BMC Bioinformatics (To appear)
(* denotes equal contribution)
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The Power of Explainability in Forecast-Informed Deep Learning Models for Flood Mitigation.
Jimeng Shi, Vitalii Stebliankin, Giri Narasimhan.
NeurIPS 2023 workshop on Climate Change AI (Poster).
[PDF]
[Code]
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Graph Transformer Network for Flood Forecasting with Heterogeneous Covariates.
Jimeng Shi, Vitalii Stebliankin, Zhaonan Wang, Shaowen Wang, Giri Narasimhan.
NSF I-GUIDE Forum in New York City, 2023 (Oral).
[PDF]
[Code]
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Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting.
Jimeng Shi, Rukmangadh Myana, Vitalii Stebliankin, Azam Shirali, Giri Narasimhan.
ECML-PKDD 2023 workshop on Advanced Analytics and Learning on Temporal Data (Oral).
[PDF]
[Code]
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Deep Learning Models for Water Level Prediction in South Florida.
Jimeng Shi*, Zeda Yin*, Rukmangadh Myana, Arturo Leon, Jayantha Obeysekera, Giri Narasimhan.
Journal of water resources planning and management (Under review).
Part of work was presented at the I-GUIDE All-Hands Meeting, Chicago in 2022.
[PDF]
[Code]
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Evaluating protein binding interfaces with transformer networks.
Vitalii Stebliankin, Azam Shirali, Prabin Baral, Jimeng Shi, Prem Chapagain, Kalai Mathee, Giri Narasimhan.
Nature Machine Intelligence (IF=25.89).
[PDF]
[Codes]
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Physic-Informed Neural Network Approach Coupled with Boundary Conditions for Solving 1D Steady Shallow Water Equations for Riverine System.
Zeda Yin, Linlong Bian, Beichao Hu, Jimeng Shi, Arturo Leon.
World Environmental and Water Resources Congress 2023 (Best paper award).
