Arnout Devos
Arnout Devos
EPFL (Swiss Federal Institute of Technology Lausanne)
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Citado por
A meta-learning approach for genomic survival analysis
YL Qiu, H Zheng, A Devos, H Selby, O Gevaert
Nature Communications 11, 1-11, 2020
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification
C Medina*, A Devos*, M Grossglauser
ICML 2020 Workshop on Automated Machine Learning (AutoML), 2020
Area and power efficient ultra-wideband transmitter based on active inductor
K Ture, A Devos, F Maloberti, C Dehollain
TCAS-II 2018: IEEE Transactions on Circuits and Systems II: Express Briefs …, 2018
Regression networks for meta-learning few-shot classification
A Devos, M Grossglauser
ICML 2020 Workshop on Automated Machine Learning (AutoML), 2020
Reproducing Meta-learning with differentiable closed-form solvers
A Devos*, S Chatel*, M Grossglauser
ReScience C Journal, 2019, 2019
Revisiting few-shot learning for facial expression recognition
AN Ciubotaru, A Devos, B Bozorgtabar, JP Thiran, M Gabrani
arXiv preprint arXiv:1912.02751, 2019
Multiphase digitally controlled oscillator for future 5G phased arrays in 90 nm CMOS
A Devos, M Vigilante, P Reynaert
NORCAS 2016: IEEE Nordic Circuits and Systems Conference (NORCAS), 1-4, 2016
Profit Maximizing Logistic Regression Modeling for Credit Scoring
A Devos, J Dhondt, E Stripling, B Baesens, S vanden Broucke, ...
DSW 2018: Proceedings of the IEEE Data Science Workshop (DSW), 125-129, 2018
Model-Agnostic Learning to Meta-Learn
A Devos*, Y Dandi*
Proceedings of Machine Learning Research 148, 155-175, 2021
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