Publications associées à Jeu de données

Fixed-wing micro UAV open data with digicam and raw INS/GNSS

Jan Skaloud, Davide Antonio Cucci, Kenneth Joseph Paul

We have recently released in the open domain data originating from a series of flights conducted with a fixed-wing micro UAV carrying high-quality small camera and navigation sensors. This data was previously used in several peer-reviewed publications. How ...

2021

Recursive Input And State Estimation: A General Framework For Learning From Time Series With Missing Data

Robert West, Alberto Garcia Duran

Time series with missing data are signals encountered in important settings for machine learning. Some of the most successful prior approaches for modeling such time series are based on recurrent neural networks that transform the input and previous state ...

IEEE2021

The effect of spokesperson attribution on public health message sharing during the COVID-19 pandemic

Robert West, Andreas Oliver Spitz, Ahmad Abu-Akel

It is urgent to understand how to effectively communicate public health messages during the COVID-19 pandemic. Previous work has focused on how to formulate messages in terms of style and content, rather than on who should send them. In particular, little ...

2021

The time course of serial dependence: an interplay between perceptual decisions and task relevant representations

Michael Herzog, David Pascucci, Gizay Ceylan

In serial dependence (SD), features of a present stimulus are judged as similar to previously presented ones. This bias is often explained by a continuity field (CF) in perception, combining similar stimuli in an extended region of space (∼ 15°) and time ( ...

SAGE Publishing2021

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Naman Goel, Amit Sharma

Training datasets for machine learning often have some form of missingness. For example, to learn a model for deciding whom to give a loan, the available training data includes individuals who were given a loan in the past, but not those who were not. This ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Superluminal Motion-Assisted Four-Dimensional Light-in-Flight Imaging

Edoardo Charbon, Andrei Ardelean, Ming-Lo Wu, Kazuhiro Morimoto

Advances in high-speed imaging techniques have opened new possibilities for capturing ultrafast phenomena such as light propagation in air or through media. Capturing light in flight in three-dimensional xyt space has been reported based on various types o ...

AMER PHYSICAL SOC2021

POSEIDON: Privacy-Preserving Federated Neural Network Learning

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Léonard Bossuat, Apostolos Pyrgelis, David Jules Froelicher, Joao André Gomes de Sá e Sousa, Sinem Sav

In this paper, we address the problem of privacy-preserving training and evaluation of neural networks in an N-party, federated learning setting. We propose a novel system, POSEIDON, the first of its kind in the regime of privacy-preserving neural network ...

INTERNET SOC2021

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

Kamiar Aminian, Mathieu Pascal Falbriard, Abolfazl Soltani

The overground speed is a key component of running analysis. Today, most speed estimation wearable systems are based on GNSS technology. However, these devices can suffer from sparse communication with the satellites and have a high-power consumption. In t ...

2021

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Jeu de données

Fixed-wing micro UAV open data with digicam and raw INS/GNSS

Recursive Input And State Estimation: A General Framework For Learning From Time Series With Missing Data

The effect of spokesperson attribution on public health message sharing during the COVID-19 pandemic

The time course of serial dependence: an interplay between perceptual decisions and task relevant representations

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Superluminal Motion-Assisted Four-Dimensional Light-in-Flight Imaging

POSEIDON: Privacy-Preserving Federated Neural Network Learning

Geodesic Distance on Optimally Regularized Functional Connectomes Uncovers Individual Fingerprints

Measurement of the inner structure of turbidity currents by ultrasound velocity profiling

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

Graph Chatbot

Chattez avec Graph Search

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

The time course of serial dependence: an interplay between perceptual decisions and task relevant representations

Measurement of the inner structure of turbidity currents by ultrasound velocity profiling

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Recursive Input And State Estimation: A General Framework For Learning From Time Series With Missing Data

Fixed-wing micro UAV open data with digicam and raw INS/GNSS

Superluminal Motion-Assisted Four-Dimensional Light-in-Flight Imaging

The effect of spokesperson attribution on public health message sharing during the COVID-19 pandemic

Geodesic Distance on Optimally Regularized Functional Connectomes Uncovers Individual Fingerprints

POSEIDON: Privacy-Preserving Federated Neural Network Learning