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X-WR-CALNAME:Biomedical Mathematics Group
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X-WR-CALDESC:Events for Biomedical Mathematics Group
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TZID:Asia/Seoul
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TZOFFSETFROM:+0900
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DTSTART:20250101T000000
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DTSTART;TZID=Asia/Seoul:20260417T100000
DTEND;TZID=Asia/Seoul:20260417T120000
DTSTAMP:20260417T015346
CREATED:20260403T080037Z
LAST-MODIFIED:20260406T060603Z
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SUMMARY:Discovering network dynamics with neural symbolic regression - Olive Cawiding
DESCRIPTION:In this tallk\, we discuss the paper “Discovering network dynamics with neural symbolic regression” by Zihan Yu et al.\, Nature Com. Science\, 2026. \nAbstract  \nNetwork dynamics are fundamental to analyzing the properties of high-dimensional complex systems and understanding their behavior. Despite the accumulation of observational data across many domains\, mathematical models exist in only a few areas with clear underlying principles. Here we show that a neural symbolic regression approach can bridge this gap by automatically deriving formulas from data. Our method reduces searches on high-dimensional networks to equivalent one-dimensional systems and uses pretrained neural networks to guide accurate formula discovery. Applied to ten benchmark systems\, it recovers the correct forms and parameters of underlying dynamics. In two empirical natural systems\, it corrects existing models of gene regulation and microbial communities\, reducing prediction error by 59.98% and 55.94%\, respectively. In epidemic transmission across human mobility networks of various scales\, it discovers dynamics that exhibit the same power-law distribution of node correlations across scales and reveal country-level differences in intervention effects. These results demonstrate that machine-driven discovery of network dynamics can enhance understandings of complex systems and advance the development of complexity science.
URL:https://www.ibs.re.kr/bimag/event/discovering-network-dynamics-with-neural-symbolic-regression-olive-cawiding/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
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