Dr. Robert Vandermeulen
Dr. Robert Vandermeulen is a Postdoctoral Researcher at BIFOLD. He earned his PhD in Electrical Engineering at the University of Michigan in 2016. Prior to working at BIFOLD Robert was a postdoctoral researcher at Technische Universität Kaiserslautern. His work focuses on deep anomaly detection and nonparametric statistics.
- Deep Anomaly Detection
- Nonparametric Density Estimation
- Nonparametric Tensor Methods
- Nonparametric Statistics
- Human vs. Neural Network Alignment
Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine Hermann, Andrew K. Lampinen, Simon Kornblith
Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller
Lukas Muttenthaler, Jonas Dippel, Lorenz Linhardt, Robert A. Vandermeulen, Simon Kornblith
Lukas Muttenthaler, Charles Yang Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira
Robert A. Vandermeulen, René Saitenmacher
The paper “Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation” by BIFOLD researcher Dr. Robert A. Vandermeulen and his colleague Dr. Antoine Ledent, Technical University Kaiserslautern, was presented at the Conference on Neural Information Processing Systems (NeurIPS 2021). Their paper provides the first solid theoretical foundations for applying low-rank methods to nonparametric density estimation.