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Valerie Vaquet
Valerie Vaquet
在 techfak.uni-bielefeld.de 的电子邮件经过验证
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Evaluating robustness of counterfactual explanations
A Artelt, V Vaquet, R Velioglu, F Hinder, J Brinkrolf, M Schilling, ...
2021 IEEE Symposium Series on Computational Intelligence (SSCI), 01-09, 2021
422021
Suitability of different metric choices for concept drift detection
F Hinder, V Vaquet, B Hammer
International Symposium on Intelligent Data Analysis, 157-170, 2022
182022
Contrasting Explanation of Concept Drift.
F Hinder, A Artelt, V Vaquet, B Hammer
ESANN, 2022
92022
Balanced sam-knn: Online learning with heterogeneous drift and imbalanced data
V Vaquet, B Hammer
Artificial Neural Networks and Machine Learning–ICANN 2020: 29th …, 2020
82020
Model-based explanations of concept drift
F Hinder, V Vaquet, J Brinkrolf, B Hammer
Neurocomputing 555, 126640, 2023
72023
Investigating intensity and transversal drift in hyperspectral imaging data
V Vaquet, P Menz, U Seiffert, B Hammer
Neurocomputing 505, 68-79, 2022
72022
Fast non-parametric conditional density estimation using moment trees
F Hinder, V Vaquet, J Brinkrolf, B Hammer
2021 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2021
72021
Contrastive explanations for explaining model adaptations
A Artelt, F Hinder, V Vaquet, R Feldhans, B Hammer
International Work-Conference on Artificial Neural Networks, 101-112, 2021
72021
On the Hardness and Necessity of Supervised Concept Drift Detection.
F Hinder, V Vaquet, J Brinkrolf, B Hammer
ICPRAM, 164-175, 2023
62023
Taking care of our drinking water: dealing with sensor faults in water distribution networks
V Vaquet, A Artelt, J Brinkrolf, B Hammer
International Conference on Artificial Neural Networks, 682-693, 2022
62022
A shape-based method for concept drift detection and signal denoising
F Hinder, J Brinkrolf, V Vaquet, B Hammer
2021 IEEE Symposium Series on Computational Intelligence (SSCI), 01-08, 2021
52021
Contrasting explanations for understanding and regularizing model adaptations
A Artelt, F Hinder, V Vaquet, R Feldhans, B Hammer
Neural Processing Letters 55 (5), 5273-5297, 2023
42023
On the change of decision boundary and loss in learning with concept drift
F Hinder, V Vaquet, J Brinkrolf, B Hammer
International Symposium on Intelligent Data Analysis, 182-194, 2023
42023
Localization of concept drift: Identifying the drifting datapoints
F Hinder, V Vaquet, J Brinkrolf, A Artelt, B Hammer
2022 International Joint Conference on Neural Networks (IJCNN), 1-9, 2022
42022
One or Two Things We know about Concept Drift--A Survey on Monitoring Evolving Environments
F Hinder, V Vaquet, B Hammer
arXiv preprint arXiv:2310.15826, 2023
32023
Online learning on non-stationary data streams for image recognition using deep embeddings
V Vaquet, F Hinder, J Vaquet, J Brinkrolf, B Hammer
2021 IEEE Symposium Series on Computational Intelligence (SSCI), 1-7, 2021
22021
Combining self-labeling and demand based active learning for non-stationary data streams
V Vaquet, F Hinder, J Brinkrolf, B Hammer
arXiv preprint arXiv:2302.04141, 2023
12023
On the change of decision boundaries and loss in learning with concept drift
F Hinder, V Vaquet, J Brinkrolf, B Hammer
arXiv preprint arXiv:2212.01223, 2022
12022
Federated learning vector quantization for dealing with drift between nodes
V Vaquet, F Hinder, J Brinkrolf, P Menz, U Seiffert, B Hammer
Bruges, 2022
12022
A remark on concept drift for dependent data
F Hinder, V Vaquet, B Hammer
International Symposium on Intelligent Data Analysis, 77-89, 2024
2024
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