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A Data-Driven Computational Framework for Identifiability and Nonlinear Dynamics Discovery in Complex Systems Data-driven modeling is essential for deciphering complex biological systems, yet its utility is often constrained by two fundamental hurdles: the inability to guarantee parameter identifiability and the high computational cost of learning nonlinear dynamics. This talk introduces a unified computational framework designed … |
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One equation helps solve three paradoxes in the spatial ecology of predators and prey In this talk I will introduce three paradoxes in the spatial ecology of predators and prey (1) Buffer Zone Paradox: Why do wolves maintain stable buffer zones for prey, even though they may be only saving prey for the neighboring packs? … |
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