2 papers
math.NA2026
Tucker Tensor Train Taylor Series
Nick Alger, Blake Christierson, Peng Chen +1
Learning derivative-accurate surrogates for implicit simulators is a key challenge in scientific machine learning. High-order Taylor surrogates have long been considered intractabl…
math.NA2025
Accelerating seismic inversion and uncertainty quantification with efficient high-rank Hessian approximations
Mathew Hu, Nick Alger, Rami Nammour +1
Efficient high-rank approximations of the Hessian can accelerate seismic full waveform inversion (FWI) and uncertainty quantification (UQ). In FWI, approximations of the inverse of…