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Found 4 papers, 2 papers with code
Semi-NMF Regularization-Based Autoencoder Training for Hyperspectral Unmixing
Hyperspectral Unmixing (HSU) refers to the procedure of decomposing measured pixel spectra into a set of constituent spectral signatures known as endmembers and a corresponding set of fractional mixing ratios.
Who Provides the Largest Megaphone? The Role of Google News in Promoting Russian State-Affiliated News Sources
Only in Russia and China do Google competitors claim more market share, with approximately 60% of Internet users in Russia preferring Yandex (compared to 40% in favor of Google) and more than 80% of China's Internet users accessing Baidu as of 2022.
Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality
We make a case that the network topology of Granger causal relations is directly inferrable from a structured sparse estimate of the internal parameters of the SRU networks trained to predict the processes$'$ time series measurements.
Decentralized Joint-Sparse Signal Recovery: A Sparse Bayesian Learning Approach
This work proposes a decentralized, iterative, Bayesian algorithm called CB-DSBL for in-network estimation of multiple jointly sparse vectors by a network of nodes, using noisy and underdetermined linear measurements.
