Jack H Buckner
I am a quantitative developing computational tools to improve our understanding of and adaptation to a changing environment.
Session
07-25
13:00
30min
UniversalDiffEq.jl: applying SciML to ecology
Jack H Buckner
UniversalDiffEq.jl provides an easy-to-use front end for building universal differential equations (UDEs). It implements and several training routines, including a novel state-space approach that increases training stability on noisy and highly variable time series data. We applied these methods to long-term environmental data sets to demonstrate their usefulness for inferring biological mechanisms from time series data and forecasting large changes in ecosystem states called regime shifts.
Methods and Applications of Scientific Machine Learning (SciML)
Main Room 3