AI Driven Pipelines for Science - From Easy To Hard

Antoine Sanchez, Viktor Schlegel, Nathan CK Wong, Christina Atchison, Anil Anthony Bharath, Christina Vagena-Pantoula, Sulaimaan Lim, Julien C Vermot

Keywords: Data Pipelines, Visual Analytics, Microscopy, Pandemic Monitoring

TL;DR: Common elements of data pipelines for science which are built using ML, rather than (the usual) data pipelines for machine learning.

Confirmation Of Submission Requirements: I submit an abstract. It uses the template provided on the submission page and is no longer than 2 pages.

Submission Number: 239