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Advances in nonlinear elliptic and parabolic pdes
NLPDES
Advances in nonlinear elliptic and parabolic pdes

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Matrix Algorithms

Exploiting Data Sparsity in Matrix Algorithms for Adaptive Optics and Seismic Imaging

Yuxi Hong, Ph.D. Student, Computer Science
Jun 7, 14:30 - 17:00

B2 R5209;

Matrix Algorithms machine learning High Performance Computing

This thesis addresses the exponential growth of experimental data and the resulting computational complexity seen in two major scientific applications, which account for most cycles consumed on today's supercomputers.

Advances in nonlinear elliptic and parabolic pdes (NLPDES)

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