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Robert A. Vandermeulen
Person information
- affiliation: TU Berlin, Germany
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2020 – today
- 2024
- [j3]Robert A. Vandermeulen
, René Saitenmacher
:
Generalized Identifiability Bounds for Mixture Models With Grouped Samples. IEEE Trans. Inf. Theory 70(4): 2746-2758 (2024) - [c15]Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller:
Set Learning for Accurate and Calibrated Models. ICLR 2024 - 2023
- [c14]Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen
, Simon Kornblith:
Human alignment of neural network representations. ICLR 2023 - [c13]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 - [i16]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 abs/2306.04507 (2023) - [i15]Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller:
Set Learning for Accurate and Calibrated Models. CoRR abs/2307.02245 (2023) - 2022
- [j2]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) - [c12]Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira:
VICE: Variational Interpretable Concept Embeddings. NeurIPS 2022 - [i14]Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart
, Francisco Pereira:
VICE: Variational Interpretable Concept Embeddings. CoRR abs/2205.00756 (2022) - [i13]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 abs/2205.11474 (2022) - [i12]Robert A. Vandermeulen, René Saitenmacher:
Generalized Identifiability Bounds for Mixture Models with Grouped Samples. CoRR abs/2207.11164 (2022) - [i11]Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith:
Human alignment of neural network representations. CoRR abs/2211.01201 (2022) - 2021
- [j1]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): 756-795 (2021) - [c11]Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen
, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller:
Explainable Deep One-Class Classification. ICLR 2021 - [c10]Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen
:
Transfer-Based Semantic Anomaly Detection. ICML 2021: 2546-2558 - [c9]Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen
, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft:
Learning Interpretable Concept Groups in CNNs. IJCAI 2021: 1061-1067 - [c8]Robert A. Vandermeulen, Antoine Ledent:
Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation. NeurIPS 2021: 12180-12193 - [i10]Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft:
Learning Interpretable Concept Groups in CNNs. CoRR abs/2109.10078 (2021) - 2020
- [c7]Lukas Ruff, Robert A. Vandermeulen
, Nico Görnitz, Alexander Binder
, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft:
Deep Semi-Supervised Anomaly Detection. ICLR 2020 - [c6]Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott:
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations. NeurIPS 2020 - [i9]Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft:
Rethinking Assumptions in Deep Anomaly Detection. CoRR abs/2006.00339 (2020) - [i8]Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott:
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations. CoRR abs/2006.07459 (2020) - [i7]Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller:
Explainable Deep One-Class Classification. CoRR abs/2007.01760 (2020) - [i6]Waleed Mustafa, Robert A. Vandermeulen, Marius Kloft:
Input Hessian Regularization of Neural Networks. CoRR abs/2009.06571 (2020) - [i5]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 abs/2009.11732 (2020) - [i4]Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen:
Deep Anomaly Detection by Residual Adaptation. CoRR abs/2010.02310 (2020) - [i3]Robert A. Vandermeulen:
Improving Nonparametric Density Estimation with Tensor Decompositions. CoRR abs/2010.02425 (2020)
2010 – 2019
- 2019
- [c5]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: 4061-4071 - [i2]Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft:
Deep Semi-Supervised Anomaly Detection. CoRR abs/1906.02694 (2019) - 2018
- [c4]Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, Marius Kloft:
Deep One-Class Classification. ICML 2018: 4390-4399 - [c3]Lucas Deecke, Robert A. Vandermeulen
, Lukas Ruff, Stephan Mandt
, Marius Kloft:
Image Anomaly Detection with Generative Adversarial Networks. ECML/PKDD (1) 2018: 3-17 - 2015
- [i1]Robert A. Vandermeulen, Clayton D. Scott:
On The Identifiability of Mixture Models from Grouped Samples. CoRR abs/1502.06644 (2015) - 2014
- [c2]Robert A. Vandermeulen, Clayton D. Scott:
Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space. NIPS 2014: 433-441 - 2013
- [c1]Robert A. Vandermeulen, Clayton D. Scott:
Consistency of Robust Kernel Density Estimators. COLT 2013: 568-591
Coauthor Index
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last updated on 2024-08-08 20:13 CEST by the dblp team
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