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ENTITY power engineering

power engineering

PulseAugur coverage of power engineering — every cluster mentioning power engineering across labs, papers, and developer communities, ranked by signal.

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RECENT · PAGE 1/1 · 6 TOTAL
  1. TOOL · CL_218880 ·

    New framework treats time series forecasting as visual inpainting task

    Researchers have introduced ICI-Time, a new framework that treats time series forecasting as a visual inpainting problem. This approach leverages the capabilities of large vision models by converting time series data in…

  2. TOOL · CL_225308 ·

    ICI-Time framework reframes time series forecasting as visual inpainting

    Researchers have developed ICI-Time, a new framework that treats time series forecasting as a visual inpainting problem. This approach utilizes large vision models by converting time series data into area charts, which …

  3. RESEARCH · CL_210243 ·

    Deep learning models benchmarked for smart meter energy forecasting

    Researchers have conducted an empirical benchmark of nine deep learning models for smart meter energy forecasting, evaluating their performance on two public datasets. The study found that while extending historical inp…

  4. RESEARCH · CL_206179 ·

    AI frameworks proposed for power system protection and operations · 2 sources tracked

    Two recent arXiv papers propose standardized frameworks for applying machine learning to power system protection and operations. The first paper introduces a seven-dimension framework to ensure comparability and auditab…

  5. RESEARCH · CL_181501 ·

    New framework bridges AI and power engineering education · 2 sources tracked

    A new framework, Engineering-Grounded AI (EGAI), has been developed to integrate artificial intelligence into power and energy systems education. This framework, presented as a collection of open, executable Jupyter not…

  6. RESEARCH · CL_65261 ·

    New method optimizes power systems using decision-calibrated prediction sets

    Researchers have developed a new method called decision-calibrated prediction sets for optimizing power system operations under uncertainty. This approach calibrates uncertainty sets based on the reliability of downstre…