Publications related to Probabilistic classification

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

2024

Probabilistic methods for neural combinatorial optimization

Nikolaos Karalias

The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

EPFL2023

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

SAGTTA: SALIENCY GUIDED TEST TIME AUGMENTATION FOR MEDICAL IMAGE SEGMENTATION ACROSS VENDOR DOMAIN SHIFT

Devavrat Tomar, Seyedbehzad Bozorgtabar

Test time augmentation has been shown to be an effective approach to combat domain shifts in deep learning. Despite their promising performance levels, the interpretability of the underlying used models is however low. Saliency maps have been widely used i ...

IEEE2023

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

Ekaterina Krymova, Markus Scholz

Background During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases an ...

Springernature2022

On Generalizations of Some Distance Based Classifiers for HDLSS Data

Soham Sarkar

In high dimension, low sample size (HDLSS) settings, classifiers based on Euclidean distances like the nearest neighbor classifier and the average distance classifier perform quite poorly if differences between locations of the underlying populations get m ...

Microtome Publishing2022

Robust Unsupervised Gaze Calibration Using Conversation and Manipulation Attention Priors

Jean-Marc Odobez, Rémy Alain Siegfried

Gaze estimation is a difficult task, even for humans. However, as humans, we are good at understanding a situation and exploiting it to guess the expected visual focus of attention of people, and we usually use this information to retrieve people's gaze. I ...

ASSOC COMPUTING MACHINERY2022

Probabilistic fatigue model for composites based on the statistical characteristics of the cycles to failure

Anastasios Vassilopoulos, Guangjian Xiang

A probabilistic model for estimating the fatigue life of composite laminates based on the mean value and standard deviation of the fatigue life is introduced here for predicting the distribution of fatigue life at any stress level for a constant stress rat ...

ELSEVIER SCI LTD2022

Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation

Jean-Marc Vesin, Adrian Luca, Etienne Pruvot

Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiot ...

FRONTIERS MEDIA SA2022

Blind as a Bat: Audible Echolocation on Small Robots

Martin Vetterli, Mihailo Kolundzija, Adrien Guillaume Olivier Hoffet, Adam James Scholefield, Frederike Dümbgen

For safe and efficient operation, mobile robots need to perceive their environment, and in particular, perform tasks such as obstacle detection, localization, and mapping. Although robots are often equipped with microphones and speakers, the audio modality ...

2022

Network Classifiers Based On Social Learning

Ali H. Sayed, Virginia Bordignon, Stefan Vlaski

This work proposes a new way of combining independently trained classifiers over space and time. Combination over space means that the outputs of spatially distributed classifiers are aggregated. Combination over time means that the classifiers respond to ...

IEEE2021

Representing graphs through data with learning and optimal transport

Hermina Petric Maretic

Graphs offer a simple yet meaningful representation of relationships between data. This representation is often used in machine learning algorithms in order to incorporate structural or geometric information about data. However, it can also be used in an i ...

EPFL2021

Advances In Morphological Neural Networks: Training, Pruning And Enforcing Shape Constraints

Nikolaos Dimitriadis

In this paper, we study an emerging class of neural networks, the Morphological Neural networks, from some modern perspectives. Our approach utilizes ideas from tropical geometry and mathematical morphology. First, we state the training of a binary morphol ...

IEEE2021

Predicting Superagers by Machine Learning Classification Based on the Functional Brain Connectome Using Resting-State Functional Magnetic Resonance Imaging

Chang-Hyun Park

Superagers are defined as older adults who have youthful memory performance comparable to that of middle-aged adults. Classifying superagers based on the brain connectome using machine learning modeling can provide important insights on the physiology unde ...

OXFORD UNIV PRESS INC2021

Classifying Dyads for Militarized Conflict Analysis

Robert West

Understanding the origins of militarized conflict is a complex, yet important undertaking. Existing research seeks to build this understanding by considering bi-lateral relationships between entity pairs (dyadic causes) and multi-lateral relationships amon ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

ComplexBeat: Breathing Rate Estimation from Complex CSI

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Andreas Toftegaard Kristensen, Sitian Li

In this paper, we explore the use of channel state information (CSI) from a WiFi system to estimate the breathing rate of a person in a room. In order to extract WiFi CSI components that are sensitive to breathing, we propose to consider the delay domain c ...

IEEE, ELECTRON DEVICES SOC & RELIABILITY GROUP2021

Continuous monitoring of propofol in human serum with fouling compensation by support vector classifier

Giovanni De Micheli, Sandro Carrara, Mandresy Ivan Ny Hanitra, Danilo Demarchi, Francesca Criscuolo, Simone Aiassa, Francesco Grassi, Tiberiu Totu, Gabriele Sandri

We present a new method for electrochemical sensing, which compensates the fouling effect of propofol through machine learning (ML) model. Direct and continuous monitoring of propofol is crucial in the development of automatic systems for control of drug i ...

Elsevier2020

Weight Erosion: An Update Aggregation Scheme for Personalized Collaborative Machine Learning

Martin Jaggi, Mary-Anne Hartley, Sai Praneeth Reddy Karimireddy, Felix Hans Michel Grimberg

Background. In medicine and other applications, the copying and sharing of data is impractical for a range of well-considered reasons. With federated learning (FL) techniques, machine learning models can be trained on data spread across several locations w ...

Springer, Cham2020

Learning One Class Representations for Face Presentation Attack Detection using Multi-channel Convolutional Neural Networks

Sébastien Marcel

Face recognition has evolved as a widely used biometric modality. However, its vulnerability against presentation attacks poses a significant security threat. Though presentation attack detection (PAD) methods try to address this issue, they often fail in ...

IEEE2020

Machine learning based detection of digital documents maliciously recaptured from displays

Touradj Ebrahimi, Evgeniy Upenik, Saleh Gholam Zadeh

We used to say “seeing is believing": this is no longer true. The digitization is changing all aspects of life and business. One of the more noticeable impacts is in how business documents are being authored, exchanged and processed. Many documents such as ...

2020