Bruno Lecouat
Bruno Lecouat
PhD student, Inria
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Cited by
Cited by
Efficient gan-based anomaly detection
H Zenati, CS Foo, B Lecouat, G Manek, VR Chandrasekhar
arXiv preprint arXiv:1802.06222, 2018
Optimistic mirror descent in saddle-point problems: Going the extra (-gradient) mile
P Mertikopoulos, B Lecouat, H Zenati, CS Foo, V Chandrasekhar, ...
International Conference on Learning Representations (ICLR), 2018
Adversarially Learned Anomaly Detection
H Zenati, M Romain, CS Foo, B Lecouat, V Chandrasekhar
IEEE International Conference on Data Mining (ICDM), 727-736, 2018
Semi-supervised learning with gans: Revisiting manifold regularization
B Lecouat, CS Foo, H Zenati, VR Chandrasekhar
International Conference on Learning Representations (ICLR) Workshop Track, 2018
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images
B Lecouat, K Chang, CS Foo, B Unnikrishnan, JM Brown, H Zenati, ...
NeurIPS Workshop on Machine Learning for Health, 2018
Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration
B Lecouat, J Ponce, J Mairal
European Conference on Computer Vision (ECCV), 2020
Manifold regularization with GANs for semi-supervised learning
B Lecouat, CS Foo, H Zenati, V Chandrasekhar
arXiv preprint arXiv:1807.04307, 2018
A Flexible Framework for Designing Trainable Priors with Adaptive Smoothing and Game Encoding
B Lecouat, J Ponce, J Mairal
Advances in Neural Information Processing Systems (NeurIPS) 33, 2020
Aliasing is your Ally: End-to-End Super-Resolution from Raw Image Bursts
B Lecouat, J Ponce, J Mairal
arXiv preprint arXiv:2104.06191, 2021
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