ติดตาม
Robert A. Vandermeulen
Robert A. Vandermeulen
Independent Researcher
ยืนยันอีเมลแล้วที่ umich.edu - หน้าแรก
ชื่อ
อ้างโดย
อ้างโดย
ปี
Deep One-Class Classification
L Ruff, R Vandermeulen, N Goernitz, L Deecke, SA Siddiqui, A Binder, ...
International Conference on Machine Learning, 4390-4399, 2018
27212018
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
11052021
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
2822020
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
1112021
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
952020
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
922019
Human alignment of neural network representations
L Muttenthaler, L Linhardt, J Dippel, RA Vandermeulen, S Kornblith
SVRHM 2022 Workshop@ NeurIPS, 2022
662022
Transfer-based semantic anomaly detection
L Deecke, L Ruff, RA Vandermeulen, H Bilen
International Conference on Machine Learning, 2546-2558, 2021
472021
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
462022
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, 50978-51007, 2023
332023
VICE: Variational Inference for Concept Embeddings
L Muttenthaler, CY Zheng, P McClure, RA Vandermeulen, MN Hebart, ...
Advances in NeurIPS, 2022
23*2022
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
An Operator Theoretic Approach to Nonparametric Mixture Models
RA Vandermeulen, CD Scott
Annals of Statistics 47 (5), 2704-2733, 2019
202019
Consistent Estimation of Identifiable Nonparametric Mixture Models from Grouped Observations
A Ritchie, RA Vandermeulen, C Scott
Advances in Neural Information Processing Systems 33, 2020
142020
Anomaly detection with generative adversarial networks, 2018
L Deecke, R Vandermeulen, L Ruff, S Mandt, M Kloft
URL https://openreview. net/forum, 2018
142018
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
ระบบไม่สามารถดำเนินการได้ในขณะนี้ โปรดลองใหม่อีกครั้งในภายหลัง
บทความ 1–20