A sequence-to-point knowledge distillation approach trains compact student models to match the short-term forecasting performance of larger teacher models while cutting model size and memory by over 10x on AI data center load data.
Solar and wind power forecasting: A comparative review of LSTM, random forest, and XGBoost models
3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3verdicts
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The paper surveys novel hardware technologies including RIS and ISAC along with learning-based resource allocation for 6G, then analyzes challenges and open questions.
The review covers types and sizing of solar cars, their power source configurations, leading solar car nations, and the main challenges facing the technology.
citing papers explorer
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Deployment-Efficient Short-Term Load Forecasting in AI Data Centers via Sequence-to-Point Knowledge Distillation
A sequence-to-point knowledge distillation approach trains compact student models to match the short-term forecasting performance of larger teacher models while cutting model size and memory by over 10x on AI data center load data.
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Comprehensive Review of Advances and Challenges in Next Generation Wireless Networks: From Novel Hardware Technologies to Learning Based Resource Allocation in 6G
The paper surveys novel hardware technologies including RIS and ISAC along with learning-based resource allocation for 6G, then analyzes challenges and open questions.
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Solar Cars: A Comprehensive Review
The review covers types and sizing of solar cars, their power source configurations, leading solar car nations, and the main challenges facing the technology.