Publications associées à Fonction logistique (Verhulst)

Cognitive workload monitoring in virtual reality based rescue missions with drones

David Atienza Alonso, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Niloofar Momeni

The use of drones in search and rescue (SAR) missions can be very cognitively demanding. Since high levels of cognitive workload can negatively affect human performance, there is a risk of compromising the mission and leading to failure with catastrophic o ...

2020

Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, David Jules Froelicher, Joao André Gomes de Sá e Sousa

Data sharing has become of primary importance in many domains such as big-data analytics, economics and medical research, but remains difficult to achieve when the data are sensitive. In fact, sharing personal information requires individuals' unconditiona ...

2020

Learning Activation Functions in Deep (Spline) Neural Networks

Michaël Unser, Pakshal Narendra Bohra, Shayan Aziznejad, Harshit Gupta, Joaquim Gonçalves Garcia Barreto Campos

We develop an efficient computational solution to train deep neural networks (DNN) with free-form activation functions. To make the problem well-posed, we augment the cost functional of the DNN by adding an appropriate shape regularization: the sum of the ...

2020

Assessing Urban Sustainability through Participatory Multi-Criteria Approaches (PMCAs): An Updated Comparative Analysis

Albert Merino

This chapter presents a comparative analysis of four Participatory Multi-Criteria Approaches (PMCAs) usually applied in sustainability assessments (SMCE, MCM, 3-SPM and INTEGRAAL). Such approaches are presented in detail and subsequently compared to each o ...

Cambridge University Press2020

Global uncertainty-sensitivity analysis on mechanistic kinetic models: From model assessment to theory-driven design of nanoparticles

Paul Bowen, Andrea Testino, Agnese Carino, Mohammad Reza Andalibi

Recently, we developed a population balance framework describing the precipitation of calcium-silicate-hydrate, a key nanomaterial in the construction industry and with potential applications in biomedicine, environmental remediation, and catalysis. In thi ...

2020

Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART

Charlotte Marie Bürki

The emission parameterization is a crucial part of numerical pollen dispersion models. This paper shows that Artificial Neural Networks (ANNs) can substantially improve the performance of the Ambrosia pollen emission in numerical pollen dispersion models s ...

PERGAMON-ELSEVIER SCIENCE LTD2019

A jamming transition from under- to over-parametrization affects generalization in deep learning

Matthieu Wyart, Stefano Spigler, Levent Dogus Sagun

In this paper we first recall the recent result that in deep networks a phase transition, analogous to the jamming transition of granular media, delimits the over- and under-parametrized regimes where fitting can or cannot be achieved. The analysis leading ...

IOP PUBLISHING LTD2019

Empirical validation of MesoHABSIM models developed with different habitat suitability criteria for bullhead cottus gobio L. as an indicator species

Giovanni De Cesare, Mikolaj Stanislaw Adamczyk, Piotr Parasiewicz

Application of instream habitat models such as the Mesohabitat Simulation Model (MesoHABSIM) is becoming increasingly popular. Such models can predict alteration to a river physical habitat caused by hydropower operation or river training. They are a tool ...

2019

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Fonction logistique (Verhulst)

Cognitive workload monitoring in virtual reality based rescue missions with drones

Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets

Learning Activation Functions in Deep (Spline) Neural Networks

Assessing Urban Sustainability through Participatory Multi-Criteria Approaches (PMCAs): An Updated Comparative Analysis

No difference in 13-year survival after medial pivot or central pivot mobile bearing total knee arthroplasty. A propensity matched comparative analysis

Global uncertainty-sensitivity analysis on mechanistic kinetic models: From model assessment to theory-driven design of nanoparticles

Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART

A jamming transition from under- to over-parametrization affects generalization in deep learning

Full-Gradient Representation for Neural Network Visualization

Empirical validation of MesoHABSIM models developed with different habitat suitability criteria for bullhead cottus gobio L. as an indicator species

Graph Chatbot

Chattez avec Graph Search

No difference in 13-year survival after medial pivot or central pivot mobile bearing total knee arthroplasty. A propensity matched comparative analysis

Assessing Urban Sustainability through Participatory Multi-Criteria Approaches (PMCAs): An Updated Comparative Analysis

Artificial neural networks can be used for Ambrosia pollen emission parameterization in COSMO-ART

Empirical validation of MesoHABSIM models developed with different habitat suitability criteria for bullhead cottus gobio L. as an indicator species

Global uncertainty-sensitivity analysis on mechanistic kinetic models: From model assessment to theory-driven design of nanoparticles

Cognitive workload monitoring in virtual reality based rescue missions with drones

Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets

Learning Activation Functions in Deep (Spline) Neural Networks

A jamming transition from under- to over-parametrization affects generalization in deep learning

Full-Gradient Representation for Neural Network Visualization