Publications by Tatjana Chavdarova

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

Martin Jaggi, Mary-Anne Hartley, Jonathan Dönz, 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

what If...? Pandemic Policy-decision-support to Guide a Cost-benefit-optimised, Country- Specific Response

Martin Jaggi, Mary-Anne Hartley, Thierry Bossy, Tatjana Chavdarova, Prakhar Gupta

Background After 18 months of responding to the COVID-19 pandemic, there is still no agreement on the optimal combination of mitigation strategies. The efficacy and collateral damage of pandemic policies are dependent on constantly evolving viral epidemiol ...

PUBLIC LIBRARY SCIENCE2022

Semantic Perturbations with Normalizing Flows for Improved Generalization

Martin Jaggi, Tatjana Chavdarova, Sebastian Urban Stich

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

Deep Generative Models and Applications

Tatjana Chavdarova

Over the past few years, there have been fundamental breakthroughs in core problems in machine learning, largely driven by advances in deep neural networks. The amount of annotated data drastically increased and supervised deep discriminative models exceed ...

EPFL2020

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

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

Stochastic Variance Reduced Gradient Optimization of Generative Adversarial Networks

François Fleuret, Tatjana Chavdarova, Martin Jaggi, Sebastian Urban Stich

2018

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

Pascal Fua, Tatjana Chavdarova, François Fleuret, 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