متابعة
Robert A. Vandermeulen
Robert A. Vandermeulen
Independent Researcher
بريد إلكتروني تم التحقق منه على umich.edu - الصفحة الرئيسية
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
Deep One-Class Classification‏
L Ruff, R Vandermeulen, N Goernitz, L Deecke, SA Siddiqui, A Binder, ...‏
International Conference on Machine Learning, 4390-4399, 2018‏
27082018
A unifying review of deep and shallow anomaly detection‏
L Ruff, JR Kauffmann, RA Vandermeulen, G Montavon, W Samek, M Kloft, ...‏
Proceedings of the IEEE 109 (5), 756-795, 2021‏
10922021
Deep semi-supervised anomaly detection‏
L Ruff, RA Vandermeulen, N Görnitz, A Binder, E Müller, KR Müller, ...‏
International Conference on Learning Representations, 2019‏
7732019
Image anomaly detection with generative adversarial networks‏
L Deecke, R Vandermeulen, L Ruff, S Mandt, M Kloft‏
Joint european conference on machine learning and knowledge discovery in …, 2018‏
2932018
Explainable deep one-class classification‏
P Liznerski, L Ruff, RA Vandermeulen, BJ Franks, M Kloft, KR Müller‏
International Conference on Learning Representations, 2020‏
2812020
Rethinking assumptions in deep anomaly detection‏
L Ruff, RA Vandermeulen, BJ Franks, KR Müller, M Kloft‏
ICML 2021 Workshop on Uncertainty & Robustness in Deep Learning, 2021‏
1072021
Machine learning in thermodynamics: Prediction of activity coefficients by matrix completion‏
F Jirasek, RAS Alves, J Damay, RA Vandermeulen, R Bamler, M Bortz, ...‏
The journal of physical chemistry letters 11 (3), 981-985, 2020‏
912020
Self-attentive, multi-context one-class classification for unsupervised anomaly detection on text‏
L Ruff, Y Zemlyanskiy, R Vandermeulen, T Schnake, M Kloft‏
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019‏
902019
Human alignment of neural network representations‏
L Muttenthaler, L Linhardt, J Dippel, RA Vandermeulen, S Kornblith‏
SVRHM 2022 Workshop@ NeurIPS, 2022‏
622022
Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images‏
P Liznerski, L Ruff, RA Vandermeulen, BJ Franks, KR Müller, M Kloft‏
Transactions on Machine Learning Research, 2022‏
452022
Transfer-based semantic anomaly detection‏
L Deecke, L Ruff, RA Vandermeulen, H Bilen‏
International Conference on Machine Learning, 2546-2558, 2021‏
452021
Improving neural network representations using human similarity judgments‏
L Muttenthaler, L Linhardt, J Dippel, RA Vandermeulen, K Hermann, ...‏
Advances in Neural Information Processing Systems 36, 2024‏
292024
Consistency of robust kernel density estimators‏
R Vandermeulen, C Scott‏
Conference on Learning Theory, 568-591, 2013‏
232013
Deep support vector data description for unsupervised and semi-supervised anomaly detection‏
L Ruff, RA Vandermeulen, N Gornitz, A Binder, E Muller, M Kloft‏
Proceedings of the ICML 2019 Workshop on Uncertainty and Robustness in Deep …, 2019‏
222019
VICE: Variational Inference for Concept Embeddings‏
L Muttenthaler, CY Zheng, P McClure, RA Vandermeulen, MN Hebart, ...‏
Advances in NeurIPS, 2022‏
21*2022
An Operator Theoretic Approach to Nonparametric Mixture Models‏
RA Vandermeulen, CD Scott‏
Annals of Statistics 47 (5), 2704-2733, 2019‏
192019
Anomaly detection with generative adversarial networks, 2018‏
L Deecke, R Vandermeulen, L Ruff, S Mandt, M Kloft‏
URL https://openreview. net/forum, 2018‏
152018
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations‏
A Ritchie, RA Vandermeulen, C Scott‏
Advances in Neural Information Processing Systems 33, 2020‏
132020
Robust kernel density estimation by scaling and projection in hilbert space‏
RA Vandermeulen, C Scott‏
Advances in Neural Information Processing Systems 27, 2014‏
132014
On the identifiability of mixture models from grouped samples‏
RA Vandermeulen, CD Scott‏
arXiv preprint arXiv:1502.06644, 2015‏
112015
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مقالات 1–20