The tremendous progress of big data acquisition and processing in the field of neural
engineering has enabled a better understanding of the patient's brain disorders with their …

Time-of-flight three-dimensional imaging is an important tool for applications such as object
recognition and remote sensing. Conventional time-of-flight three-dimensional imaging …

When recovering a sparse signal from noisy compressive linear measurements, the
distribution of the signal's non-zero coefficients can have a profound effect on recovery …

Sound source localization with sensor arrays involves the estimation of the direction-of-
arrival (DOA) from a limited number of observations. Compressive sensing (CS) solves such …

The supplementary appendix contains additional details about AMP algorithms for
rectangular matrices and the rectangular generalized invariant universality class of …

Universality of approximate message passing with semirandom matrices Page 1 The
Annals of Probability 2023, Vol. 51, No. 5, 1616–1683 https://doi.org/10.1214/23-AOP1628 …

A recent line of work in high-dimensional statistics working under the Gaussian mixture
hypothesis has led to a number of results in the context of empirical risk minimization …

A classic problem is the estimation of a set of parameters from measurements collected by
only a few sensors. The number of sensors is often limited by physical or economical …

We propose 'Tapestry', a single-round pooled testing method with application to COVID-19
testing using quantitative Reverse Transcription Polymerase Chain Reaction (RT-PCR) that …

Compressive sensing involves 3 main processes: signal sparse representation, linear
encoding or measurement collection, and nonlinear decoding or sparse recovery. In the …