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UID:pretalx-juliacon-2026-7JNHHN@pretalx.com
DTSTART;TZID=CET:20260814T100000
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DESCRIPTION:The Weak-form Estimation of Non-linear Dynamics (WENDy) framewo
 rk is a recently developed approach for parameter estimation and inference
  of systems of ordinary differential equations (ODEs). Prior work demonstr
 ated WENDy to be robust\, computationally efficient\, and accurate. Prior 
 work was limited to ODEs which are linear-in-parameters and utilized a les
 s robust cost function. Our Julia package includes implementations of prev
 iously developed weak-form methods as well as novel extensions. Notably\, 
  [WENDy.jl](https://github.com/nrummel/WENDy.jl) now accommodates systems 
 of a more general class of ODEs that are nonlinear-in-parameters. This is 
 made possible through the new WENDy-MLE which approximates the maximum lik
 elihood estimator. Also\, this code facilitates a Bayesian framework with 
 custom objective priors through the new WENDy-MAP algorithms  and maximum 
 a posterior estimator respectively. Both estimators are computed via local
  non-convex optimization methods. \n\nOur work is made possible by the ava
 ilability of analytic expressions for the approximate weak-likelihood func
 tion and its first and second order derivatives. These algorithms have bet
 ter accuracy\, a substantially larger domain of convergence\, and are ofte
 n faster than other weak form methods and the conventional output error le
 ast squares method. Moreover\, we extend the framework to accommodate data
  corrupted by multiplicative log-normal noise.
DTSTAMP:20260502T104552Z
LOCATION:Room 6
SUMMARY:Weak-form Estimation of Nonlinear Dynamics (WENDy) in Julia - Nicho
 las Rummel
URL:https://pretalx.com/juliacon-2026/talk/7JNHHN/
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