Visualizing Graph Neural Networks with CorGIE: Corresponding a Graph to Its Embedding

1 code implementation • 24 Jun 2021 • Zipeng Liu, Yang Wang, Jürgen Bernard, Tamara Munzner

Graph neural networks (GNNs) are a class of powerful machine learning tools that model node relations for making predictions of nodes or links.

ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion

no code implementations • 2 Oct 2019 • Andreas Hinterreiter, Peter Ruch, Holger Stitz, Martin Ennemoser, Jürgen Bernard, Hendrik Strobelt, Marc Streit

The confusion matrix is an established way for visualizing these class errors, but it was not designed with temporal or comparative analysis in mind.

Active Learning Model Selection +1

Visual-Interactive Similarity Search for Complex Objects by Example of Soccer Player Analysis

no code implementations • 9 Mar 2017 • Jürgen Bernard, Christian Ritter, David Sessler, Matthias Zeppelzauer, Jörn Kohlhammer, Dieter Fellner

In a visual-interactive interface, users are able to label pairs of soccer players with respect to their subjective notion of similarity.

Active Learning Information Retrieval +1