Abstract: This paper introduces a novel optimized hybrid model combining Long Short-Term Memory (LSTM) and Transformer deep learning architectures designed for power load forecasting. It leverages the ...
The West Virginia Mountaineers got off to a slow start in Morgantown against Robert Morris last week. In the first half, WVU looked sloppy, but as they got comfortable, the Mountaineers started to ...
Abstract: Power load forecasting is the foundation of maintaining power grid stability, and can assist in decision-making to reduce operating costs. Fine-grained long sequence load forecasting ...
PyTorch is a popular open-source machine learning framework that provides a wide range of tools for building neural networks. It is widely used in academic and industry research, and is also used in ...
DeepAR (LSTM+Gaussian) and N-BEATS models forecast GOOG (2015–2025) with covariates, scaling, and robust splits. Trained via PyTorch Lightning (early stopping, checkpoint, LR scheduling). Grid search ...
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