Machine Learning Methods in Visualisation for Big Data 2022

@inproceedings {N200AB:2022,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, DanielNabney, IanPeltonen, Jaakko},
title = {{Visual Exploration of Neural Network Projection Stability}},
author = {Bredius, Carlo and Tian, Zonglin and Telea, Alexandru},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-182-3},
pages = {1-55 pages},
DOI = {10.2312/mlvis.20221068}
}
@inproceedings {N20009:2022,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, DanielNabney, IanPeltonen, Jaakko},
title = {{Saliency Clouds: Visual Analysis of Point Cloud-oriented Deep Neural Networks in DeepRL for Particle Physics}},
author = {Mulawade, Raju Ningappa and Garth, Christoph and Wiebel, Alexander},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-182-3},
pages = {7-115 pages},
DOI = {10.2312/mlvis.20221069}
}
@inproceedings {N20073:2022,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, DanielNabney, IanPeltonen, Jaakko},
title = {{ViNNPruner: Visual Interactive Pruning for Deep Learning}},
author = {Schlegel, Udo and Schiegg, Samuel and Keim, Daniel A.},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-182-3},
pages = {13-175 pages},
DOI = {10.2312/mlvis.20221070}
}