Robert A. Vandermeulen

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 31

Top Topics

Anomaly Detection

Density Estimation

Top Venues

Publications

Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller
Set Learning for Accurate and Calibrated Models. ICLR (2024)
Robert A. Vandermeulen, René Saitenmacher
Generalized Identifiability Bounds for Mixture Models With Grouped Samples. IEEE Trans. Inf. Theory 70 (4) (2024)
Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller
Set Learning for Accurate and Calibrated Models. CoRR (2023)
Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith
Improving neural network representations using human similarity judgments. CoRR (2023)
Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. 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)
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. CoRR (2022)
Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira
VICE: Variational Interpretable Concept Embeddings. NeurIPS (2022)
Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith
Human alignment of neural network representations. CoRR (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. Trans. Mach. Learn. Res. 2022 (2022)
Robert A. Vandermeulen, René Saitenmacher
Generalized Identifiability Bounds for Mixture Models with Grouped Samples. CoRR (2022)
Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira
VICE: Variational Interpretable Concept Embeddings. CoRR (2022)
Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
Learning Interpretable Concept Groups in CNNs. CoRR (2021)
Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
Learning Interpretable Concept Groups in CNNs. IJCAI (2021)
Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen
Transfer-Based Semantic Anomaly Detection. ICML (2021)
Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller
Explainable Deep One-Class Classification. ICLR (2021)
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. Proc. IEEE 109 (5) (2021)
Robert A. Vandermeulen, Antoine Ledent
Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation. NeurIPS (2021)
Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen
Deep Anomaly Detection by Residual Adaptation. CoRR (2020)
Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations. NeurIPS (2020)
Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations. CoRR (2020)
Waleed Mustafa, Robert A. Vandermeulen, Marius Kloft
Input Hessian Regularization of Neural Networks. CoRR (2020)
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. CoRR (2020)
Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft
Deep Semi-Supervised Anomaly Detection. ICLR (2020)
Robert A. Vandermeulen
Improving Nonparametric Density Estimation with Tensor Decompositions. CoRR (2020)
Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller
Explainable Deep One-Class Classification. CoRR (2020)
Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft
Rethinking Assumptions in Deep Anomaly Detection. CoRR (2020)
Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft
Deep Semi-Supervised Anomaly Detection. CoRR (2019)
Lukas Ruff, Yury Zemlyanskiy, Robert A. Vandermeulen, Thomas Schnake, Marius Kloft
Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text. ACL (1) (2019)
Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, Marius Kloft
Deep One-Class Classification. ICML (2018)
Lucas Deecke, Robert A. Vandermeulen, Lukas Ruff, Stephan Mandt, Marius Kloft
Image Anomaly Detection with Generative Adversarial Networks. ECML/PKDD (1) (2018)
Robert A. Vandermeulen, Clayton D. Scott
On The Identifiability of Mixture Models from Grouped Samples. CoRR (2015)
Robert A. Vandermeulen, Clayton D. Scott
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space. NIPS (2014)
Robert A. Vandermeulen, Clayton D. Scott
Consistency of Robust Kernel Density Estimators. COLT (2013)