Search Results for author:
Found 5 papers, 2 papers with code
An Edge-Cloud Integrated Framework for Flexible and Dynamic Stream Analytics
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).
Reproducible and Portable Big Data Analytics in the Cloud
We propose and develop an open-source toolkit that supports 1) fully automated end-to-end execution and reproduction via a single command, 2) automatic data and configuration storage for each execution, 3) flexible client modes based on user preferences, 4) execution history query, and 5) simple reproduction of existing executions in the same environment or a different environment.
Sea Ice Forecasting using Attention-based Ensemble LSTM
Accurately forecasting Arctic sea ice from subseasonal to seasonal scales has been a major scientific effort with fundamental challenges at play.
Scalable and Hybrid Ensemble-Based Causality Discovery
Causality discovery mines cause-effect relationships among different variables of a system and has been widely used in many disciplines including climatology and neuroscience.
A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classification
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.
