April 17, 2023, 8:02 p.m. | M Atemkeng, S Perkins, E Seck, S Makhathini, O Smirnov, L Bester, B Hugo

cs.LG updates on arXiv.org arxiv.org

This work proposes to reduce visibility data volume using a
baseline-dependent lossy compression technique that preserves smearing at the
edges of the field-of-view. We exploit the relation of the rank of a matrix and
the fact that a low-rank approximation can describe the raw visibility data as
a sum of basic components where each basic component corresponds to a specific
Fourier component of the sky distribution. As such, the entire visibility data
is represented as a collection of data matrices …

approximation arxiv astro collection components compression data distribution exploit low matrix radio raw reduce scale tensor visibility work

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US