Publications de Tatjana Chavdarova

DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

Martin Jaggi, Mary-Anne Hartley, Juliane Dervaux, Tatjana Chavdarova, Daniel Mueller, Julien Niklas Heitmann, Daniel Hinjos García

The interpretation of lung auscultation is highly subjective and relies on non-specific nomenclature. Computer-aided analysis has the potential to better standardize and automate evaluation. We used 35.9 hours of auscultation audio from 572 pediatric outpa ...

NATURE PORTFOLIO2023

Semantic Perturbations with Normalizing Flows for Improved Generalization

Martin Jaggi, Sebastian Urban Stich, Tatjana Chavdarova

Data augmentation is a widely adopted technique for avoiding overfitting when training deep neural networks. However, this approach requires domain-specific knowledge and is often limited to a fixed set of hard-coded transformations. Recently, several work ...

IEEE2021

Reducing Noise in GAN Training with Variance Reduced Extragradient

François Fleuret, Tatjana Chavdarova

We study the effect of the stochastic gradient noise on the training of generative adversarial networks (GANs) and show that it can prevent the convergence of standard game optimization methods, while the batch version converges. We address this issue with ...

2019

WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection

Pascal Fua, François Fleuret, Tatjana Chavdarova, Andrii Maksai, Cijo Jose, Stéphane Bouquet

People detection methods are highly sensitive to occlusions between pedestrians, which are extremely frequent in many situations where cameras have to be mounted at a limited height. The reduction of camera prices allows for the generalization of static mu ...

IEEE2018

SGAN: An Alternative Training of Generative Adversarial Networks

François Fleuret, Tatjana Chavdarova

The Generative Adversarial Networks (GANs) have demonstrated impressive performance for data synthesis, and are now used in a wide range of computer vision tasks. In spite of this success, they gained a reputation for being difficult to train, what results ...

IEEE2018

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Tatjana Chavdarova

DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

Semantic Perturbations with Normalizing Flows for Improved Generalization

Deep Generative Models and Applications

Reducing Noise in GAN Training with Variance Reduced Extragradient

WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection

SGAN: An Alternative Training of Generative Adversarial Networks

Graph Chatbot

Chattez avec Graph Search

Deep Generative Models and Applications

DeepBreath-automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries

Semantic Perturbations with Normalizing Flows for Improved Generalization

Reducing Noise in GAN Training with Variance Reduced Extragradient

SGAN: An Alternative Training of Generative Adversarial Networks

WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection