Robert Schwarzenberg
Robert Schwarzenberg
Machine Learning Engineer, Tiplu GmbH
Verified email at
Cited by
Cited by
Layerwise relevance visualization in convolutional text graph classifiers
R Schwarzenberg, M Hübner, D Harbecke, C Alt, L Hennig
arXiv preprint arXiv:1909.10911, 2019
Cube-cut: vertebral body segmentation in MRI-data through cubic-shaped divergences
R Schwarzenberg, B Freisleben, C Nimsky, J Egger
PloS one 9 (4), e93389, 2014
Interactive-cut: real-time feedback segmentation for translational research
J Egger, T Lüddemann, R Schwarzenberg, B Freisleben, C Nimsky
Computerized Medical Imaging and Graphics 38 (4), 285-295, 2014
Abstractive text summarization based on language model conditioning and locality modeling
D Aksenov, J Moreno-Schneider, P Bourgonje, R Schwarzenberg, ...
arXiv preprint arXiv:2003.13027, 2020
A cube-based approach to segment vertebrae in MRI-acquisitions
R Schwarzenberg, B Freisleben, R Kikinis, C Nimsky, J Egger
Proceedings of Bildverarbeitung für die Medizin (BVM), 69-74, 2013
Neural vector conceptualization for word vector space interpretation
R Schwarzenberg, L Raithel, D Harbecke
arXiv preprint arXiv:1904.01500, 2019
MOLI: Smart conversation agent for mobile customer service
G Zhao, J Zhao, Y Li, C Alt, R Schwarzenberg, L Hennig, S Schaffer, ...
Information 10 (2), 63, 2019
Question answering for technical customer support
Y Li, Q Miao, J Geng, C Alt, R Schwarzenberg, L Hennig, C Hu, F Xu
Natural Language Processing and Chinese Computing: 7th CCF International …, 2018
Saliency map verbalization: Comparing feature importance representations from model-free and instruction-based methods
N Feldhus, L Hennig, MD Nasert, C Ebert, R Schwarzenberg, S Möller
arXiv preprint arXiv:2210.07222, 2022
Thermostat: A large collection of NLP model explanations and analysis tools
N Feldhus, R Schwarzenberg, S Möller
arXiv preprint arXiv:2108.13961, 2021
Efficient explanations from empirical explainers
R Schwarzenberg, N Feldhus, S Möller
arXiv preprint arXiv:2103.15429, 2021
Learning explanations from language data
D Harbecke, R Schwarzenberg, C Alt
arXiv preprint arXiv:1808.04127, 2018
Train, sort, explain: Learning to diagnose translation models
R Schwarzenberg, D Harbecke, V Macketanz, E Avramidis, S Möller
arXiv preprint arXiv:1903.12017, 2019
In-memory distributed training of linear-chain conditional random fields with an application to fine-grained named entity recognition
R Schwarzenberg, L Hennig, H Hemsen
Language Technologies for the Challenges of the Digital Age: 27th …, 2018
Constructing natural language explanations via saliency map verbalization
N Feldhus, L Hennig, MD Nasert, C Ebert, R Schwarzenberg, S Möller
arXiv preprint arXiv:2210.07222, 2022
Evaluating German transformer language models with syntactic agreement tests
K Zaczynska, N Feldhus, R Schwarzenberg, A Gabryszak, S Möller
arXiv preprint arXiv:2007.03765, 2020
Detecting covariate drift with explanations
S Castle, R Schwarzenberg, M Pourvali
CCF International Conference on Natural Language Processing and Chinese …, 2021
Pattern-guided integrated gradients
R Schwarzenberg, S Castle
arXiv preprint arXiv:2007.10685, 2020
Cross-lingual Neural Vector Conceptualization
L Raithel, R Schwarzenberg
Natural Language Processing and Chinese Computing: 8th CCF International …, 2019
Semi-Automatic, Graph-Based Vertebra Segmentation in MRI Data
R Schwarzenberg
Department of Mathematics and Computer Science, University of Marburg Germany, 2012
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