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pro vyhledávání: '"Mechanistic models"'
Understanding the mechanisms of interactions within cells, tissues, and organisms is crucial to driving developments across biology and medicine. Mathematical modeling is an essential tool for simulating biological systems and revealing biochemical r
Externí odkaz:
http://arxiv.org/abs/2408.05395
Autor:
Nguyen, Tan T.
This review examines theoretical assumptions and computational models of event comprehension, tracing the evolution from discourse comprehension theories to contemporary event cognition frameworks. The review covers key discourse comprehension accoun
Externí odkaz:
http://arxiv.org/abs/2409.18992
Autor:
Plank, Michael J., Simpson, Matthew J.
Parameter inference and uncertainty quantification are important steps when relating mathematical models to real-world observations, and when estimating uncertainty in model predictions. However, methods for doing this can be computationally expensiv
Externí odkaz:
http://arxiv.org/abs/2403.01678
Akademický článek
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Inferring parameters of macro-kinetic growth models, typically represented by Ordinary Differential Equations (ODE), from the experimental data is a crucial step in bioprocess engineering. Conventionally, estimates of the parameters are obtained by f
Externí odkaz:
http://arxiv.org/abs/2312.03166
Comparing Data-Driven and Mechanistic Models for Predicting Phenology in Deciduous Broadleaf Forests
Understanding the future climate is crucial for informed policy decisions on climate change prevention and mitigation. Earth system models play an important role in predicting future climate, requiring accurate representation of complex sub-processes
Externí odkaz:
http://arxiv.org/abs/2401.03960
Mechanistic growth models play a major role in bioprocess engineering, design, and control. Their reasonable predictive power and their high level of interpretability make them an essential tool for computer aided engineering methods. Additionally, s
Externí odkaz:
http://arxiv.org/abs/2312.03427