The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms

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Aerosol transmission remains a major challenge for control of respiratory viruses, particularly those causing recurrent epidemics, like influenza A virus (IAV). These viruses are rarely expelled alone, but instead are embedded in a consortium of microorgan ...

We focus on distinctive data-driven measures of the fate of ongoing epidemics. The relevance of our pursuit is suggested by recent results proving that the short-term temporal evolution of infection spread is described by an epidemicity index related to th ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

Influenza is an infectious respiratory illness caused by influenza viruses. Every year, it causes up to one billion cases of disease worldwide. Despite its high disease burden, the transmission pathway of influenza remains subject to debate. There is incre ...

The World Health Organization highlights the urgent need to address the global threat posed by antibiotic-resistant bacteria. Efficient and rapid detection of bacterial response to antibiotics and their virulence state is crucial for the effective treatmen ...

Mitigating the energy requirements of artificial intelligence requires novel physical substrates for computation. Phononic metamaterials have vanishingly low power dissipation and hence are a prime candidate for green, always-on computers. However, their u ...

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

Monitoring the health of complex industrial assets is crucial for safe and efficient operations. Health indicators that provide quantitative real-time insights into the health status of industrial assets over time serve as valuable tools for, e.g., fault d ...

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

In the realm of point cloud scene understanding, particularly in indoor scenes, objects are arranged following human habits, resulting in objects of certain semantics being closely positioned and displaying notable inter-object correlations. This can creat ...

Background and Objective: Cough audio signal classification is a potentially useful tool in screening for respiratory disorders, such as COVID-19. Since it is dangerous to collect data from patients with contagious diseases, many research teams have turned ...

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 ...

Background. Respiratory syncytial virus (RSV) is associated with acute respiratory infection. We sought to identify RSV variants associated with prolonged infection. ...

The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms

Chattez avec Graph Search

Stability of influenza A virus in droplets and aerosols is heightened by the presence of commensal respiratory bacteria

Epidemicity indices and reproduction numbers from infectious disease data in connected human populations

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Robust machine learning for neuroscientific inference

Meta-learning to address diverse Earth observation problems across resolutions

Understanding generalization and robustness in modern deep learning

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Inactivation of influenza A virus in expiratory droplets and aerosol particles and the associated physicochemical drivers

Machine learning method for the classification of the state of living organisms' oscillations

In-Sensor Passive Speech Classification with Phononic Metamaterials

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

Predicting the long-term collective behaviour of fish pairs with deep learning

Learning Informative Health Indicators Through Unsupervised Contrastive Learning

Topics in statistical physics of high-dimensional machine learning

Random matrix methods for high-dimensional machine learning models

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

A semi-supervised algorithm for improving the consistency of crowdsourced datasets: The COVID-19 case study on respiratory disorder classification

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

Viral Genetic Determinants of Prolonged Respiratory Syncytial Virus Infection Among Infants in a Healthy Term Birth Cohort