Concept
Hyperparameter
Related publications (7)
Estimating muscle activation from EMG using deep learning-based dynamical systems models
Objective. To study the neural control of movement, it is often necessary to estimate how muscles are activated across a variety of behavioral conditions. One approach is to try extracting the underlying neural command signal to muscles by applying latent ...
2022Bayesian Uncertainty Quantification of Physical Models in Thermal-Hydraulics System Codes
Nuclear thermal-hydraulics (TH) system codes use several parametrized physical or empirical models to describe complex two-phase flow phenomena. The reliability of their predictions is as such primarily affected by the uncertainty associated with the param ...
EPFL2018A Versatile Noise Performance Metric for Electrical Impedance Tomography Algorithms
Jean-Philippe Thiran, Fabian Braun, Martin Proença
Electrical impedance tomography (EIT) is an emerging technology for real-time monitoring of patients under mechanical ventilation. EIT has the potential to offer continuous medical monitoring while being noninvasive, radiation free, and low cost. Due to th ...
Ieee-Inst Electrical Electronics Engineers Inc2017Online Collaborative Prediction of Regional Vote Results
Patrick Thiran, Matthias Grossglauser, Mohammad Emtiyaz Khan, Vincent Etter
We consider online predictions of vote results, where regions across a country vote on an issue under discussion. Such online predictions before and during the day of the vote are useful to media agencies, polling institutes, and political parties, e.g., t ...
IEEE2016A Mobile World of Security
Security in mobile communications is a topic of increasing relevance in everyday life. We all use mobile devices for everyday communications, maybe even for exchanging confidential information with the work place. This requires security systems that are re ...
EPFL2011On the calibration of hydrological models in ungauged basins: A framework for integrating hard and soft hydrological information
This paper presents a calibration framework based on the generalized likelihood uncertainty estimation (GLUE) that can be used to condition hydrological model parameter distributions in scarcely gauged river basins, where data is uncertain, intermittent or ...
American Geophysical Union2009