Automated graph learning is a method that aims at discovering the best hyper-parameter and neural architecture configuration for different graph tasks/data without manual design.

Class activation guide is a module which uses weak localization information from the instrument activation maps to guide the verb and target recognition. 

Image source: [Nwoye et al.](https://arxiv.org/pdf/2007.05405v1.pdf)

Recognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets

AutoGL

An adaptive graph learning method for automated molecular interactions and properties predictions

Ensemble clustering, also called consensus clustering, has
been attracting much attention in recent years, aiming to combine multiple base clustering algorithms into a better and more consensus clustering. Due to its good performance, ensemble clustering plays a vital role in many research areas, such as community detection and bioinformatics.

Source	An adaptive graph learning method for automated molecular interactions and properties predictions
Year	2000
Data Source	CC BY-SA - https://paperswithcode.com

Viet-Anh on Software

What is: Automated Graph Learning?

Viet-Anh on Software