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Found 4 papers, 3 papers with code
AA-Forecast: Anomaly-Aware Forecast for Extreme Events
Moreover, the framework employs a dynamic uncertainty optimization algorithm that reduces the uncertainty of forecasts in an online manner.
Protoformer: Embedding Prototypes for Transformers
This paper proposes Protoformer, a novel self-learning framework for Transformers that can leverage problematic samples for text classification.
Ranked #1 on
Text Classification
on arXiv-10
A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19
To this end, it is essential to develop an interpretable forecast model that supports managerial and organizational decision-making.
Work-in-progress: a deep learning strategy for I/O scheduling in storage systems
Under the big data era, there is a crucial need to improve the performance of storage systems for data-intensive applications.
