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Found 4 papers, 3 papers with code
TTML: tensor trains for general supervised machine learning
This work proposes a novel general-purpose estimator for supervised machine learning (ML) based on tensor trains (TT).
Automatic rational approximation and linearization of nonlinear eigenvalue problems
The method uses the AAA method by Nakatsukasa, S\`{e}te, and Trefethen to approximate the nonlinear eigenvalue problem by a rational eigenvalue problem and is embedded in the state space representation of a rational polynomial by Su and Bai.
Numerical Analysis 65F15, 65F50, 15A22, 47A56, 47J10
Unifying time evolution and optimization with matrix product states
In particular, our method is compatible with any Hamiltonian for which DMRG can be implemented efficiently and DMRG is obtained as a special case of imaginary time evolution with infinite time step.
Quantum Physics Strongly Correlated Electrons
Low-rank matrix completion by Riemannian optimization---extended version
We propose a new algorithm for matrix completion that minimizes the least-square distance on the sampling set over the Riemannian manifold of fixed-rank matrices.
Optimization and Control Differential Geometry Numerical Analysis
