Implementation of tensor network algorithms for completion of sparsely sampled quantum states
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Updated
May 9, 2024 - Python
Implementation of tensor network algorithms for completion of sparsely sampled quantum states
Leverage score based Tensor Completion algorithm, SPLATT
This repository aims to design the coded apertures for rolling shutter video. The reconstruction is performed using the captured compressive projection using two methods, interpolation, and tensor compleition.
Implements the code from the publication A distributed proximal gradient descent methods for tensor completion
Tensor Factorization Based Method for Tensor Completion with Spatio-Temporal Characterization
Master's coursework project on Advanced Machine Learning at HCMUS: Tensor Networks and Their Applications
Python code and data for "Attention-Guided Low-Rank Tensor Completion"
Low-rank tensor recovery via non-convex regularization, structured factorization and spatio-temporal characteristics
Nonconvex Optimization for Third Order Tensor Completion Under Wavelet Transform
My graduate research on low-rank matrix and tensor completion, and maximum volume algorithms for finding dominant submatrices.
Python code for "Deep Unfolding Tensor Rank Minimization with Generalized Detail Injection for Pansharpening"
T-product factorization based method for matrix and tensor completion problems
KDD2021: Code for MTC algorithm. We use coarse granular data and partially observed data to (low-rank) recover the fine granular data.
Laplacian-enhanced tensor learning for large-scale spatiotemporal traffic data kriging (estimation)
This project aims to realize the tensor completion algorithms via tensor ring decomposition.
Python code and data for "Deep Unrolled Low-Rank Tensor Completion for High Dynamic Range Imaging"
MATLAB code for the coarray tensor completion-based 2-D DOA estimation algorithm
A collection of tensor completion algorithms
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