Search Results for author: Jean-François Couchot

Found 10 papers, 2 papers with code

Differentially Private Multivariate Time Series Forecasting of Aggregated Human Mobility With Deep Learning: Input or Gradient Perturbation?

1 code implementation1 May 2022 Héber H. Arcolezi, Jean-François Couchot, Denis Renaud, Bechara Al Bouna, Xiaokui Xiao

As shown in the results, differentially private deep learning models trained under gradient or input perturbation achieve nearly the same performance as non-private deep learning models, with loss in performance varying between $0. 57\%$ to $2. 8\%$.

Decision Making Multivariate Time Series Forecasting +1

Well-supported phylogenies using largest subsets of core-genes by discrete particle swarm optimization

no code implementations25 Jun 2017 Reem Alsrraj, Bassam AlKindy, Christophe Guyeux, Laurent Philippe, Jean-François Couchot

The number of complete chloroplastic genomes increases day after day, making it possible to rethink plants phylogeny at the biomolecular era.

Binary Particle Swarm Optimization versus Hybrid Genetic Algorithm for Inferring Well Supported Phylogenetic Trees

no code implementations31 Aug 2016 Bassam AlKindy, Bashar Al-Nuaimi, Christophe Guyeux, Jean-François Couchot, Michel Salomon, Reem Alsrraj, Laurent Philippe

Considering a subset of close plant species defined according to their chloroplasts, the phylogenetic tree that can be inferred by their core genes is not necessarily well supported, due to the possible occurrence of problematic genes (i. e., homoplasy, incomplete lineage sorting, horizontal gene transfers, etc.)

Neural Networks and Chaos: Construction, Evaluation of Chaotic Networks, and Prediction of Chaos with Multilayer Feedforward Networks

no code implementations21 Aug 2016 Jacques M. Bahi, Jean-François Couchot, Christophe Guyeux, Michel Salomon

The purpose of this paper is to establish, based on a rigorous theoretical framework, an equivalence between chaotic iterations according to Devaney and a particular class of neural networks.

Steganalysis via a Convolutional Neural Network using Large Convolution Filters for Embedding Process with Same Stego Key

2 code implementations25 May 2016 Jean-François Couchot, Raphaël Couturier, Christophe Guyeux, Michel Salomon

For the past few years, in the race between image steganography and steganalysis, deep learning has emerged as a very promising alternative to steganalyzer approaches based on rich image models combined with ensemble classifiers.

Multimedia

Hybrid Genetic Algorithm and Lasso Test Approach for Inferring Well Supported Phylogenetic Trees based on Subsets of Chloroplastic Core Genes

no code implementations20 Apr 2015 Bassam AlKindy, Christophe Guyeux, Jean-François Couchot, Michel Salomon, Christian Parisod, Jacques M. Bahi

The amount of completely sequenced chloroplast genomes increases rapidly every day, leading to the possibility to build large scale phylogenetic trees of plant species.

Gene Similarity-based Approaches for Determining Core-Genes of Chloroplasts

no code implementations17 Dec 2014 Bassam AlKindy, Christophe Guyeux, Jean-François Couchot, Michel Salomon, Jacques M. Bahi

More precisely, we proposed to use genes names, sequence similarities, or both, insured either from NCBI or from DOGMA annotation tools.

Clustering

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