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Robert A. Vandermeulen

Technical University of Berlin

Generalized Identifiability Bounds for Mixture Models with Grouped Samples


Jul 22, 2022
Robert A. Vandermeulen, René Saitenmacher


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Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images


May 23, 2022
Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft

* 37 pages, preprint. arXiv admin note: text overlap with arXiv:2006.00339 

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VICE: Variational Interpretable Concept Embeddings


May 13, 2022
Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira


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VICE: Variational Inference for Concept Embeddings


May 04, 2022
Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira


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Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation


Apr 02, 2022
Robert A. Vandermeulen, Antoine Ledent

* Accepted to NeurIPS 2021 

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Learning Interpretable Concept Groups in CNNs


Sep 21, 2021
Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft


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Improving Nonparametric Density Estimation with Tensor Decompositions


Oct 06, 2020
Robert A. Vandermeulen

* 20 pages, 1 table 

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Deep Anomaly Detection by Residual Adaptation


Oct 05, 2020
Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen


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A Unifying Review of Deep and Shallow Anomaly Detection


Sep 28, 2020
Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller

* 36 pages, preprint; references added 

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Input Hessian Regularization of Neural Networks


Sep 14, 2020
Waleed Mustafa, Robert A. Vandermeulen, Marius Kloft

* Workshop on "Beyond first-order methods in ML systems" at the 37th International Conference on Machine Learning, Vienna, Austria, 2020 

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