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Found 4 papers, 1 papers with code
Routing Recovery for UAV Networks with Deliberate Attacks: A Reinforcement Learning based Approach
The unmanned aerial vehicle (UAV) network is popular these years due to its various applications.
Learning and Dynamical Models for Sub-seasonal Climate Forecasting: Comparison and Collaboration
The SSF dataset constructed for the work, dynamical model predictions, and code for the ML models are released along with the paper for the benefit of the broader machine learning community.
Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances
Sub-seasonal climate forecasting (SSF) focuses on predicting key climate variables such as temperature and precipitation in the 2-week to 2-month time scales.
High-Dimensional Dependency Structure Learning for Physical Processes
We compare ACLIME-ADMM with baselines on both synthetic data simulated by partial differential equations (PDEs) that model advection-diffusion processes, and real data (50 years) of daily global geopotential heights to study information flow in the atmosphere.
