| ... | ... | @@ -37,7 +37,7 @@ Virtual Meeting using [BigBlueButton](https://webconf.fz-juelich.de/b/wen-mym-pj |
|
|
|
* R. Roscher, B. Bohn, M. F. Duarte and J. Garcke, "Explainable Machine Learning for Scientific Insights and Discoveries," in IEEE Access, vol. 8, pp. 42200-42216, 2020 https://doi.org/10.1109/ACCESS.2020.2976199
|
|
|
|
|
|
|
|
* Special guest: [Ribana Roscher](http://rs.ipb.uni-bonn.de/) who will talk about concepts foe Explainable AI and the paper
|
|
|
|
* [slides](`files/JournalClub/xaiSciences_roscher.pdf`)
|
|
|
|
* slides can be downloaded [here](`files/JournalClub/xaiSciences_roscher.pdf`)
|
|
|
|
|
|
|
|
__Short CV__<br>
|
|
|
|
Ribana Roscher is Junior Professor of Remote Sensing at University of Bonn since 2015 and held an interims Professorship for Semantic Technologies at University of Osnabrück in 2019 and 2020. Before that she was PostDoc Fellow at FU Berlin and University of Bonn. She was visiting researcher at UCLA and the Fields Institute for Research in Mathematical Science. Ribana studied Geodesy at University of Bonn and perused a PhD in Photogrammetry and Remote on ’Sequential learning using incremental import vector machines for semantic segmentation’. Her research focuses on Ocean remote sensing and plant phenotyping, Explainable and interpretable machine learning, (Deep) representation/feature learning, and Theory-guided/informed machine learning.
|
| ... | ... | @@ -185,4 +185,4 @@ A training schedule using filter pruning and orthogonal reinitialization |
|
|
|
|
|
|
|
|
|
|
|
---
|
|
|
|
last change: 19.10.2020 sw |
|
|
|
last change: 17.11.2020 sw |
