Leila Arras
Leila Arras
Research Associate, Fraunhofer HHI, Germany
Verified email at hhi.fraunhofer.de - Homepage
Cited by
Cited by
"What is relevant in a text document?": An interpretable machine learning approach
L Arras, F Horn, G Montavon, KR Müller, W Samek
PLOS ONE 12 (8), e0181142, 2017
Explaining Recurrent Neural Network Predictions in Sentiment Analysis
L Arras, G Montavon, KR Müller, W Samek
EMNLP 2017 Workshop on Computational Approaches to Subjectivity, Sentiment …, 2017
Explaining Predictions of Non-Linear Classifiers in NLP
L Arras, F Horn, G Montavon, KR Müller, W Samek
ACL 2016 Representation Learning for NLP (Rep4NLP), 1-7, 2016
Evaluating Recurrent Neural Network Explanations
L Arras, A Osman, KR Müller, W Samek
ACL 2019 BlackboxNLP Workshop (oral), Analyzing & Interpreting Neural …, 2019
Explaining and Interpreting LSTMs
L Arras, J Arjona-Medina, M Widrich, G Montavon, M Gillhofer, KR Müller, ...
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, LNCS …, 2019
Towards Ground Truth Evaluation of Visual Explanations
A Osman, L Arras, W Samek
arXiv:2003.07258, 2020
Causes of Outcome Learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome
A Rieckmann, P Dworzynski, L Arras, S Lapuschkin, W Samek, OA Arah, ...
medRxiv 2020.12.10.20225243, 2020
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