PhysAttNet: enhancing predictive performance in industrial and astrophysical time series via physics-informed attention
Read the original at arxiv.org→arXiv:2608.07681v1 Announce Type: new Abstract: Accurate and robust time series forecasting is essential in many applications involving physical processes, such as manufacturing monitoring and astrophysical event...
Original headline: "PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention"
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- Aug 11, 04:00 UTC arXiv cs.LG lead source PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention