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The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond
These competitions focus on accurate energy consumption forecasting and the importance of interpretability in understanding the underlying factors.
General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Societal Implications and Responsible Governance
Most applications of Artificial Intelligence (AI) are designed for a confined and specific task.
AutoEn: An AutoML method based on ensembles of predefined Machine Learning pipelines for supervised Traffic Forecasting
Intelligent Transportation Systems are producing tons of hardly manageable traffic data, which motivates the use of Machine Learning (ML) for data-driven applications, such as Traffic Forecasting (TF).
Local-Global Methods for Generalised Solar Irradiance Forecasting
There are many proposed methods for forecasting solar irradiance / solar power production.
Comparison and Evaluation of Methods for a Predict+Optimize Problem in Renewable Energy
As both forecasting and optimization are difficult problems in their own right, relatively few research has been done in this area.
L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout
(b) We also introduce a simple meta-level dropout technique that reduces meta-level overfitting in several few-shot learning approaches.
On the use of convolutional neural networks for robust classification of multiple fingerprint captures
In our experiments, convolutional neural networks yielded better accuracy and penetration rate than state-of-the-art classifiers based on explicit feature extraction.
