Conference and Journal Papers
- Lukas Muttenthaler, Robert A. Vandermeulen*, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller, Set Learning for Accurate and Calibrated Models, ICLR 2024
- Robert A. Vandermeulen and René Saitenmacher, Generalized Identifiability Bounds for Mixture Models with Grouped Samples, IEEE: Transactions on Information Theory 2024 (to appear)
- Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine Hermann, Andrew K. Lampinen, Simon Kornblith, Improving neural network representations using human similarity judgments, NeurIPS 2023
- Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith, Human alignment of neural network representations, ICLR 2023
- Lukas Muttenthaler, Charles Yang Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N Hebart, Francisco Pereira, VICE: Variational Interpretable Concept Embeddings, NeurIPS 2022
- Philipp Liznerski, Lukas Ruff*, Robert A. Vandermeulen*, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft, Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images, TMLR 2022
- Robert A. Vandermeulen and Antoine Ledent, Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation, NeurIPS 2021
- Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen, Transfer-Based Semantic Anomaly Detection, ICML 2021 [CODE]
- Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, DamianBorth, Marius Kloft, Learning Interpretable Concept Groups in CNNs, IJCAI 2021
- Philipp Liznerski, Lukas Ruff*, Robert A. Vandermeulen*, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller, Explainable Deep One-Class Classification, ICLR 2021 [CODE]
- Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller, A Unifying Review of Deep and Shallow Anomaly Detection, Proceedings of the IEEE 2021
- Alexander Ritchie, Robert A. Vandermeulen*, Clayton Scott, Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations, NeurIPS 2020
- Fabian Jirasek, Rodrigo A. S. Alves, Julie Damay, Robert A. Vandermeulen, Robert Bamler, Michael Bortz, Stephan Mandt, Marius Kloft, Hans Hasse, Machine Learning in Thermodynamics: Prediction of Activity Coefficients by Matrix Completion, Journal of Physical Chemistry Letters 2020
- Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft, Deep Semi-Supervised Anomaly Detection, ICLR 2020 [CODE]
- Robert A. Vandermeulen and Clayton D. Scott, An Operator Theoretic Approach to Nonparametric Mixture Models, Annals of Statistics 2019
- Lukas Ruff, Yury Zemlyanskiy, Robert Vandermeulen, Thomas Schnake, Marius Kloft, Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text, ACL 2019 [CODE]
- Lukas Ruff, Robert Vandermeulen*, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel Müller, Marius Kloft, Deep One-Class Classification, ICML 2018 [CODE]
- Lucas Deecke, Robert Vandermeulen*, Lukas Ruff, Stephan Mandt, Marius Kloft, Image Anomaly Detection with Generative Adversarial Networks, ECML PKDD 2018
- Robert A. Vandermeulen and Clayton D. Scott, Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space, NeurIPS 2014
- Robert A. Vandermeulen and Clayton D. Scott, Consistency of Robust Kernel Density Estimators, COLT 2013
* = equal contribution as first author
Workshop Papers
- Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Simon Kornblith, Human alignment of neural network representations, NeurIPS: SVRHM Workshop 2022
- Lukas Ruff, Robert A. Vandermeulen*, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft, Rethinking Assumptions in Deep Anomaly Detection, ICML: Workshop on Uncertainty & Robustness in Deep Learning 2021
- Robert A. Vandermeulen, René Saitenmacher, Alexander Ritchie, A Proposal for Supervised Density Estimation, NeurIPS: Preregistration Workshop 2020
- Waleed Mustafa, Robert A. Vandermeulen, Marius Kloft, Input Hessian Regularization of Neural Networks, ICML Workshop: Beyond First Order Methods in ML Systems 2020
- Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Marius Kloft, Deep Support Vector Data Description for Unsupervised and Semi-Supervised Anomaly Detection, ICML Workshop: Uncertainty & Robustness in Deep Learning 2019
- Robert A. Vandermeulen and Clayton D. Scott, An Operator Theoretic Approach to Nonparametric Mixture Models (VIDEO), Information Theory and Applications 2016
Misc.
- Robert A. Vandermeulen, Sample Complexity Using Infinite Multiview Models, 2023
- Robert A. Vandermeulen, Improving Nonparametric Density Estimation with Tensor Decompositions, 2020
- Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen, Deep Anomaly Detection by Residual Adaptation, 2020
- Lukas Ruff, Robert A. Vandermeulen*, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft, Rethinking Assumptions in Deep Anomaly Detection, 2020
- Robert A. Vandermeulen and Clayton D. Scott, On The Identifiability of Mixture Models from Grouped Samples, 2015
* = equal contribution as first author