Robert A. Vandermeulen

39 papers A* 14Journal 22Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Dimension-Independent Rates for Structured Neural Density Estimation. ICML Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam
2025	J	`jnl`	PMODE: Theoretically Grounded and Modular Mixture Modeling. CoRR Robert A. Vandermeulen
2024	A*	`conf`	Breaking the curse of dimensionality in structured density estimation. NeurIPS Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam
2024	J	`jnl`	Breaking the curse of dimensionality in structured density estimation. CoRR Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam
2024	J	`jnl`	Dimension-independent rates for structured neural density estimation. CoRR Robert A. Vandermeulen, Wai Ming Tai, Bryon Aragam
2024	J	`jnl`	Generalized Identifiability Bounds for Mixture Models With Grouped Samples. IEEE Trans. Inf. Theory Robert A. Vandermeulen, René Saitenmacher
2024	A*	`conf`	Set Learning for Accurate and Calibrated Models. ICLR Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller
2023	A*	`conf`	Human alignment of neural network representations. ICLR Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith
2023	A*	`conf`	Improving neural network representations using human similarity judgments. NeurIPS Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith
2023	J	`jnl`	Improving neural network representations using human similarity judgments. CoRR Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith
2023	J	`jnl`	Set Learning for Accurate and Calibrated Models. CoRR Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller
2022	J	`jnl`	Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images. CoRR Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft
2022	J	`jnl`	Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images. Trans. Mach. Learn. Res. Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft
2022	J	`jnl`	Generalized Identifiability Bounds for Mixture Models with Grouped Samples. CoRR Robert A. Vandermeulen, René Saitenmacher
2022	J	`jnl`	Human alignment of neural network representations. CoRR Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith
2022	A*	`conf`	VICE: Variational Interpretable Concept Embeddings. NeurIPS Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira
2022	J	`jnl`	VICE: Variational Interpretable Concept Embeddings. CoRR Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira
2021	J	`jnl`	A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
2021	A*	`conf`	Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation. NeurIPS Robert A. Vandermeulen, Antoine Ledent
2021	A*	`conf`	Explainable Deep One-Class Classification. ICLR Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller
2021	A*	`conf`	Learning Interpretable Concept Groups in CNNs. IJCAI Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
2021	J	`jnl`	Learning Interpretable Concept Groups in CNNs. CoRR Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft
2021	A*	`conf`	Transfer-Based Semantic Anomaly Detection. ICML Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen
2020	J	`jnl`	A Unifying Review of Deep and Shallow Anomaly Detection. CoRR Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
2020	A*	`conf`	Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations. NeurIPS Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott
2020	J	`jnl`	Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations. CoRR Alexander Ritchie, Robert A. Vandermeulen, Clayton D. Scott
2020	J	`jnl`	Deep Anomaly Detection by Residual Adaptation. CoRR Lucas Deecke, Lukas Ruff, Robert A. Vandermeulen, Hakan Bilen
2020	A*	`conf`	Deep Semi-Supervised Anomaly Detection. ICLR Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft
2020	J	`jnl`	Explainable Deep One-Class Classification. CoRR Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus-Robert Müller
2020	J	`jnl`	Improving Nonparametric Density Estimation with Tensor Decompositions. CoRR Robert A. Vandermeulen
2020	J	`jnl`	Input Hessian Regularization of Neural Networks. CoRR Waleed Mustafa, Robert A. Vandermeulen, Marius Kloft
2020	J	`jnl`	Rethinking Assumptions in Deep Anomaly Detection. CoRR Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus-Robert Müller, Marius Kloft
2019	J	`jnl`	Deep Semi-Supervised Anomaly Detection. CoRR Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft
2019	—	`conf`	Self-Attentive, Multi-Context One-Class Classification for Unsupervised Anomaly Detection on Text. ACL (1) Lukas Ruff, Yury Zemlyanskiy, Robert A. Vandermeulen, Thomas Schnake, Marius Kloft
2018	A*	`conf`	Deep One-Class Classification. ICML Lukas Ruff, Nico Görnitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Robert A. Vandermeulen, Alexander Binder, Emmanuel Müller, Marius Kloft
2018	—	`conf`	Image Anomaly Detection with Generative Adversarial Networks. ECML/PKDD (1) Lucas Deecke, Robert A. Vandermeulen, Lukas Ruff, Stephan Mandt, Marius Kloft
2015	J	`jnl`	On The Identifiability of Mixture Models from Grouped Samples. CoRR Robert A. Vandermeulen, Clayton D. Scott
2014	—	`conf`	Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space. NIPS Robert A. Vandermeulen, Clayton D. Scott
2013	A*	`conf`	Consistency of Robust Kernel Density Estimators. COLT Robert A. Vandermeulen, Clayton D. Scott