Applying Taylor mode AD in nonlinear equations, ODEs and more
Songchen Tan
Solving problems like nonlinear equations and differential equations can often benefit from higher-order derivative info. Using TaylorDiff.jl, we could efficiently compute higher-order derivatives in Taylor mode, thereby developing solvers with higher accuracy while maintaining a relatively low cost. We demonstrate a scalable nonlinear solver with third-order convergence and cost comparable to Newton's method, as well as ongoing work of high accuracy implicit Taylor solver for ODEs.
Symbolic-Numeric Computing and Compiler-Enhanced Algorithms
Main Room 2
