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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
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Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 1
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portfolio
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publications
Tunnel effect in CNNS: image reconstruction from max switch locations
Published in IEEE Signal Processing Letters, 2016
Use Google Scholar for full citation
Recommended citation: Matthieu Saint, Laura Rieger, Morten Hannemose, Junmo Kim, "Tunnel effect in CNNS: image reconstruction from max switch locations." IEEE Signal Processing Letters, 2016.
Separable explanations of neural network decisions
Published in Explainable and Interpretable Models in Computer Vision and Machine Learning, 2017
Recommended citation: Laura Rieger, "Separable explanations of neural network decisions." Explainable and Interpretable Models in Computer Vision and Machine Learning, 2017. https://orbit.dtu.dk/en/publications/id(1a8c2782-79cc-418b-97ff-ae97cec0b6e9).html
Tunnel Effect in CNNs: Image Reconstruction from Max Switch Locations
Published in IEEE Signal Processing Letters, 2017
Use Google Scholar for full citation
Recommended citation: M. {De La Roche Saint Andre}, L. Rieger, M. Hannemose, J. Kim, "Tunnel Effect in CNNs: Image Reconstruction from Max Switch Locations." IEEE Signal Processing Letters, 2017.
Structuring Neural Networks for More Explainable Predictions
Published in In the proceedings of Explainable and Interpretable Models in Computer Vision and Machine Learning, 2018
Access paper here Access non-final version here
Recommended citation: Laura Rieger, Pattarawat Chormai, Gr{\'{e}}goire Montavon, Lars Hansen, Klaus-Robert M{\"{u}}ller, "Structuring Neural Networks for More Explainable Predictions." In the proceedings of Explainable and Interpretable Models in Computer Vision and Machine Learning, 2018. http://link.springer.com/10.1007/978-3-319-98131-4{\_}5
Aggregating explanation methods for stable and robust explainability
Published in arXiv preprint arXiv:1903.00519, 2019
Use Google Scholar for full citation
Recommended citation: Laura Rieger, Lars Hansen, "Aggregating explanation methods for stable and robust explainability." arXiv preprint arXiv:1903.00519, 2019.
Interpretability in Intelligent Systems A New Concept?
Published in In the proceedings of Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 2019
Access paper here Access non-final version here
Recommended citation: Lars Hansen, Laura Rieger, "Interpretability in Intelligent Systems A New Concept?." In the proceedings of Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 2019. http://link.springer.com/10.1007/978-3-030-28954-6{\_}3
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge
Published in arXiv preprint arXiv:1909.13584, 2019
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Recommended citation: Laura Rieger, Chandan Singh, W Murdoch, Bin Yu, "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge." arXiv preprint arXiv:1909.13584, 2019.
Aggregating explanation methods for stable and robust explainability
Published in arxiv, 2019
Recommended citation: Laura Rieger, Lars Hansen, "Aggregating explainability methods for neural networks stabilizes explanations." arxiv, 2019. http://arxiv.org/abs/1903.00519
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge
Published in Preprint, 2019
Recommended citation: Laura Rieger, Chandan Singh, W. Murdoch, Bin Yu, "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge." arxiv, 2019. http://arxiv.org/abs/1909.13584
talks
Opening the black box - how to interpret machine learning functions and their decisions
Published:
An introduction to explaining black box machine learning models with applications in computer vision
Explaining neural networks
Published:
teaching
02450 Introduction in Machine Learning and Data Mining
Master course, DTU, DTU Compute, 2018
Basic machine learning algorithms and their applications (Teaching language: English)
02461 Introduction to Intelligent Systems
Undergraduate course, DTU, DTU Compute, 2018
Assisted with teaching fundamentals of data science to bachelor students (Teaching language: Danish)