Explaining Deep Graph Networks via Input Perturbation.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3165618
Abstract: Deep graph networks (DGNs) are a family of machine learning models for structured data which are finding heavy application in life sciences (drug repurposing, molecular property predictions) and on social network data (recommendation systems). The… read more here.
Keywords: deep graph; via input; networks via; explaining deep ... See more keywords
Explaining Deep Learning Models Applied in Histopathology: Current Developments and the Path to Sustainability
Sign Up to like & getrecommendations! Published in 2024 at "Studies in health technology and informatics"
DOI: 10.3233/shti240579
Abstract: The digital pathology landscape is in continuous expansion. The digitalization of slides using WSIs (Whole Slide Images) fueled the capacity of automatic support for diagnostics. The paper presents an overview of the current state of… read more here.
Keywords: deep learning; learning models; models applied; histopathology ... See more keywords