A Data Scalable Augmented Lagrangian KKT Preconditioner for Large-Scale Inverse Problems. - Nick Alger; Umberto Villa; Tan Bui-Thanh; Omar Ghattas (SIAM J. Sci. Comput., 2017)

Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators. - Nick Alger; Vishwas Rao; Aaron Myers; Tan Bui-Thanh; Omar Ghattas (SIAM J. Sci. Comput., 2019)

Low Rank Saddle Free Newton: Algorithm and Analysis. - Thomas O'Leary-Roseberry; Nick Alger; Omar Ghattas (CoRR, 2020)

Tensor Train Construction From Tensor Actions, With Application to Compression of Large High Order Derivative Tensors. - Nick Alger; Peng Chen 024; Omar Ghattas (SIAM J. Sci. Comput., 2020)

Point spread function approximation of high rank Hessians with locally supported non-negative integral kernels. - Nick Alger; Tucker Hartland; Noemi Petra; Omar Ghattas (CoRR, 2023)

Point Spread Function Approximation of High-Rank Hessians with Locally Supported Nonnegative Integral Kernels. - Nick Alger; Tucker Hartland; Noemi Petra; Omar Ghattas (SIAM J. Sci. Comput., 2024)

Accelerating seismic inversion and uncertainty quantification with efficient high-rank Hessian approximations. - Mathew Hu; Nick Alger; Rami Nammour; Omar Ghattas (CoRR, 2025)