activity
20172022
most citedAddressing Failure Prediction by Learning Model Confidence

106 citations · 151 across the 7 of their papers we have counts for

collaborators

18 papers

cs.CV2022

Swapping Semantic Contents for Mixing Images

Rémy Sun, Clément Masson, Gilles Hénaff +2

Deep architecture have proven capable of solving many tasks provided a sufficient amount of labeled data. In fact, the amount of available labeled data has become the principal bot…

cs.LG2022

Towards efficient feature sharing in MIMO architectures

Rémy Sun, Alexandre Ramé, Clément Masson +2

Multi-input multi-output architectures propose to train multiple subnetworks within one base network and then average the subnetwork predictions to benefit from ensembling for free…

eess.IV202118 cited

U-Net Transformer: Self and Cross Attention for Medical Image Segmentation

Olivier Petit, Nicolas Thome, Clément Rambour +1

Medical image segmentation remains particularly challenging for complex and low-contrast anatomical structures. In this paper, we introduce the U-Transformer network, which combine…

cs.CV2020

Confidence Estimation via Auxiliary Models

Charles Corbière, Nicolas Thome, Antoine Saporta +3

Reliably quantifying the confidence of deep neural classifiers is a challenging yet fundamental requirement for deploying such models in safety-critical applications. In this paper…

stat.ML2020

Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity

Vincent Le Guen, Nicolas Thome

Probabilistic forecasting consists in predicting a distribution of possible future outcomes. In this paper, we address this problem for non-stationary time series, which is very ch…

cs.CV2020

Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction

Vincent Le Guen, Nicolas Thome

Leveraging physical knowledge described by partial differential equations (PDEs) is an appealing way to improve unsupervised video prediction methods. Since physics is too restrict…