Abstract: Robust matrix completion refers to recovering a low-rank matrix given a subset of the entries corrupted by gross errors, and has various applications since many real-world signals can be ...
Abstract: We present a regularized inversion method for 3-D magnetotelluric (MT) data with axial anisotropic conductivities based on the edge-based finite element (FE) method. The Gauss–Newton (GN) ...
Tensordyne says logarithmic computing could reduce AI inference costs and power demands, offering an alternative to conventional chip designs.
Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...
Algebraic multiscale solver for flow in heterogeneous porous media by Yixuan Wang and Tchelepi.pdf An Improved Non-Traditional Finite Element Formulation for Solving the Elliptic Interface Problems by ...
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