6 papers
Faster Computation of Entropic Optimal Transport via Stable Low Frequency Modes
Reda Chhaibi, Serge Gratton, Samuel Vaiter
In this paper, we propose an accelerated version for the Sinkhorn algorithm, which is the reference method for computing the solution to Entropic Optimal Transport. Its main draw-b…
Feature Representation Transferring to Lightweight Models via Perception Coherence
Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang +3
In this paper, we propose a method for transferring feature representation to lightweight student models from larger teacher models. We mathematically define a new notion called \t…
Convolutional Rectangular Attention Module
Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang +3
In this paper, we introduce a novel spatial attention module that can be easily integrated to any convolutional network. This module guides the model to pay attention to the most d…
CNN-based Compressor Mass Flow Estimator in Industrial Aircraft Vapor Cycle System
Justin Reverdi, Sixin Zhang, Saïd Aoues +3
In Vapor Cycle Systems, the mass flow sensor playsa key role for different monitoring and control purposes. However,physical sensors can be inaccurate, heavy, cumbersome, expensive…
Training More Robust Classification Model via Discriminative Loss and Gaussian Noise Injection
Hai-Vy Nguyen, Fabrice Gamboa, Sixin Zhang +3
Robustness of deep neural networks to input noise remains a critical challenge, as naive noise injection often degrades accuracy on clean (uncorrupted) data. We propose a novel tra…
Combining Statistical Depth and Fermat Distance for Uncertainty Quantification
Hai-Vy Nguyen, Fabrice Gamboa, Reda Chhaibi +3
We measure the Out-of-domain uncertainty in the prediction of Neural Networks using a statistical notion called ``Lens Depth'' (LD) combined with Fermat Distance, which is able to…