ABSTRACT: Variational methods are highly valuable computational tools for solving high-dimensional quantum systems. In this paper, we explore the effectiveness of three variational methods: density ...
Abstract: Broadband sensor array problems can be formulated using parahermitian polynomial matrices, and the optimal solution to these problems can be based on the eigenvalue decomposition (EVD) of ...
This code implement the stabilization algorithm described in Y.Mao, J.Gilles, "Non rigid geometric distortions correction - Application to Atmospheric Turbulence Stabilization", Inverse Problems and ...
Multi-matrix invariants, or equivalently the scalar multi-trace operators of N=4 super Yang-Mills with U(N) gauge symmetry, are in one-to-one correspondence with the elements of the permutation ...
The subject of periodic Jacobi matrices on trees has evoked interest among mathematical physicists, analysts, and number theorists. We introduce a function of use in the study of these objects and ...
Large language models (LLMs), including GPT-4, LLaMA, and PaLM are pushing the boundaries of artificial intelligence. The inference latency of LLMs plays an important role because of LLMs integration ...
The program solves 2D steady-state and transient problems of structural analysis (linear-elasticity) and thermal analysis (conductive and convective heat transfer) with isoparametric and isogeometric ...
Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique that transforms a dataset into one with fewer columns, useful for creating a graph of ...
Computing the inverse of a matrix is one of the most important operations in machine learning. If some matrix A has shape n-by-n, then its inverse matrix Ai is n-by-n and the matrix product of Ai * A ...
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