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08/18/2022
Discovering Bugs in Vision Models using Off-the-shelf Image Generation and Captioning
Automatically discovering failures in vision models under real-world set...
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03/30/2020
Improving out-of-distribution generalization via multi-task self-supervised pretraining
Self-supervised feature representations have been shown to be useful for...
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02/21/2020
An end-to-end approach for the verification problem: learning the right distance
In this contribution, we augment the metric learning setting by introduc...
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11/13/2019
Self-supervised representation learning from electroencephalography signals
The supervised learning paradigm is limited by the cost - and sometimes ...
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11/03/2019
Adversarial target-invariant representation learning for domain generalization
In many applications of machine learning, the training and test set data...
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06/20/2019
Cross-Subject Statistical Shift Estimation for Generalized Electroencephalography-based Mental Workload Assessment
Assessment of mental workload in real world conditions is key to ensure ...
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01/24/2019
Multi-objective training of Generative Adversarial Networks with multiple discriminators
Recent literature has demonstrated promising results for training Genera...
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01/23/2019
Learning to navigate image manifolds induced by generative adversarial networks for unsupervised video generation
In this work, we introduce a two-step framework for generative modeling ...
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07/31/2018