首页|Optimizing ODE-derived Synthetic Data for Transfer Learning in Dynamical Biologi cal Systems
Optimizing ODE-derived Synthetic Data for Transfer Learning in Dynamical Biologi cal Systems
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – According to news reporting based on a preprint abstract, our journalists obtained thefollowing quote sourced from bi orxiv.org:“Motivation: Successfully predicting the development of biological systems can l ead to advances invarious research fields, such as cellular biology and epidemi ology. While machine learning has proven itscapabilities in generalizing the un derlying non-linear dynamics of such systems, unlocking its predictivepower is often restrained by the limited availability of large, curated datasets.
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