24 citations · 28 across the 12 of their papers we have counts for
6 papers · 1 filter
FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources
Md Sirajul Islam, Isabelle G Chapman, N I Md Ashafuddula +4
Federated Learning (FL) enables collaborative intelligence across decentralized data source devices in a privacy-preserving way. While substantial research attention has been drawn…
M3R: Localized Rainfall Nowcasting with Meteorology-Informed MultiModal Attention
Sanjeev Panta, Rhett M Morvant, Xu Yuan +2
Accurate and timely rainfall nowcasting is crucial for disaster mitigation and water resource management. Despite recent advances in deep learning, precipitation prediction remains…
Revisiting the Seasonal Trend Decomposition for Enhanced Time Series Forecasting
Sanjeev Panta, Xu Yuan, Li Chen +1
Time series forecasting presents significant challenges in real-world applications across various domains. Building upon the decomposition of the time series, we enhance the archit…
Incentive-Compatible Federated Learning with Stackelberg Game Modeling
Simin Javaherian, Bryce Turney, Li Chen +1
Federated Learning (FL) has gained prominence as a decentralized machine learning paradigm, allowing clients to collaboratively train a global model while preserving data privacy.…
GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models
Jiadong Lou, Xu Yuan, Rui Zhang +3
Graph neural networks (GNNs) have exhibited superior performance in various classification tasks on graph-structured data. However, they encounter the potential vulnerability from…
An Open and Large-Scale Dataset for Multi-Modal Climate Change-aware Crop Yield Predictions
Fudong Lin, Kaleb Guillot, Summer Crawford +3
Precise crop yield predictions are of national importance for ensuring food security and sustainable agricultural practices. While AI-for-science approaches have exhibited promisin…