research
∙
08/22/2023
Expecting The Unexpected: Towards Broad Out-Of-Distribution Detection
Improving the reliability of deployed machine learning systems often inv...
share
research
∙
05/09/2023
StarCoder: may the source be with you!
The BigCode community, an open-scientific collaboration working on the r...
research
∙
01/06/2023
A CAD System for Colorectal Cancer from WSI: A Clinically Validated Interpretable ML-based Prototype
The integration of Artificial Intelligence (AI) and Digital Pathology ha...
research
∙
10/04/2022
CADet: Fully Self-Supervised Anomaly Detection With Contrastive Learning
Handling out-of-distribution (OOD) samples has become a major stake in t...
research
∙
08/30/2022
Constraining Representations Yields Models That Know What They Don't Know
A well-known failure mode of neural networks corresponds to high confide...
research
∙
05/17/2022
Monotonicity Regularization: Improved Penalties and Novel Applications to Disentangled Representation Learning and Robust Classification
We study settings where gradient penalties are used alongside risk minim...
research
∙
06/25/2021
Domain Conditional Predictors for Domain Adaptation
Learning guarantees often rely on assumptions of i.i.d. data, which will...
research
∙
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...
research
∙
01/25/2020
Multi-task self-supervised learning for Robust Speech Recognition
Despite the growing interest in unsupervised learning, extracting meanin...
research
∙
11/09/2019
Fully Quantizing a Simplified Transformer for End-to-end Speech Recognition
While significant improvements have been made in recent years in terms o...
research
∙
11/03/2019
Adversarial target-invariant representation learning for domain generalization
In many applications of machine learning, the training and test set data...
research
∙
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 ...
research
∙
01/24/2019
Multi-objective training of Generative Adversarial Networks with multiple discriminators
Recent literature has demonstrated promising results for training Genera...
research
∙
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 ...
research
∙
11/07/2018
Generative Adversarial Speaker Embedding Networks for Domain Robust End-to-End Speaker Verification
This article presents a novel approach for learning domain-invariant spe...
research
∙
07/31/2018
Online Adaptative Curriculum Learning for GANs
Generative Adversarial Networks (GANs) can successfully learn a probabil...
research
∙
02/21/2018