Robert A. Vandermeulen

Max Planck Institute for the History of Science — Germany

Computer Science · Physical Sciences

12h-index1.5kcitations49works1.82yr avg
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Research Topics

Anomaly Detection Techniques and Applications(13), Statistical Methods and Inference(10), Bayesian Methods and Mixture Models(7), Network Security and Intrusion Detection(5), Adversarial Robustness in Machine Learning(5)

Publications49 total

Cancer Detection in Breast MRI Screening via Explainable AI Anomaly Detection
Radiology·2025· 8 citedOpen Access
Dimension-independent rates for structured neural density estimation
arXiv (Cornell University)·2024Open Access
Breaking the curse of dimensionality in structured density estimation
arXiv (Cornell University)·2024Open Access
Generalized Identifiability Bounds for Mixture Models With Grouped Samples
IEEE Transactions on Information Theory·2024· 1 citedOpen Access
Breaking the curse of dimensionality in structured density estimation
2024
Set Learning for Accurate and Calibrated Models
arXiv (Cornell University)·2023Open Access
Improving neural network representations using human similarity judgments
arXiv (Cornell University)·2023· 10 citedOpen Access
Sample Complexity Using Infinite Multiview Models
arXiv (Cornell University)·2023· 1 citedOpen Access
Human alignment of neural network representations
arXiv (Cornell University)·2022· 15 citedOpen Access
Generalized Identifiability Bounds for Mixture Models with Grouped Samples
arXiv (Cornell University)·2022Open Access
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images
arXiv (Cornell University)·2022· 13 citedOpen Access
VICE: Variational Interpretable Concept Embeddings
arXiv (Cornell University)·2022· 14 citedOpen Access
Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric\n Density Estimation
arXiv (Cornell University)·2022· 2 citedOpen Access
Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation
Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University)·2022· 2 citedOpen Access
Learning Interpretable Concept Groups in CNNs
2021· 5 citedOpen Access
Transfer-Based Semantic Anomaly Detection
Edinburgh Research Explorer (University of Edinburgh)·2021· 5 citedOpen Access
Explainable Deep One-Class Classification
arXiv (Cornell University)·2021· 18 citedOpen Access
Deep Anomaly Detection by Residual Adaptation
arXiv (Cornell University)·2020· 2 citedOpen Access
Input Hessian Regularization of Neural Networks
arXiv (Cornell University)·2020· 4 citedOpen Access
Explainable Deep One-Class Classification
arXiv (Cornell University)·2020· 94 citedOpen Access
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Frequent Co-authors

Marius Kloft(12), A Cession-Fossion(12), Lukas Ruff(10), Clayton Scott(7), Lucas Deecke(4), Philipp Liznerski(4), Billy Joe Franks(4), Klaus‐Robert Müller(4), Lukas Muttenthaler(4), Antoine Ledent(3), J Lecomte(3), J Lecomte(3), Wai Ming Tai(3), Bryon Aragam(3), Alexander Binder(2), Emmanuel Müller(2), Stephan Mandt(2), Jonas Dippel(2), Lorenz Linhardt(2), Simon Kornblith(2)