Machine learning from limited data: Predicting biological dynamics under a time-varying external input

Autor:	Kang, Hoony, Srinivasan, Keshav, Losert, Wolfgang
Rok vydání:	2024
Předmět:	Physics - Biological Physics Physics - Computational Physics Physics - Data Analysis Statistics and Probability
Druh dokumentu:	Working Paper
Popis:	Reservoir computing (RC) is known as a powerful machine learning approach for learning complex dynamics from limited data. Here, we use RC to predict highly stochastic dynamics of cell shapes. We find that RC is able to predict the steady state climate from very limited data. Furthermore, the RC learns the timescale of transients from only four observations. We find that these capabilities of the RC to act as a dynamic twin allows us to also infer important statistics of cell shape dynamics of unobserved conditions. Comment: Rephrasing, corrected sectioning, added 1 missing reference
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2408.07998 Zobrazit plný text záznamu View this record from Arxiv