Sparse-Coding

2026-04-11-intelligence-du-regard

2026-03-05-ue-natural-cognition

2026-02-10-biomplus

2026-02-03-ai-and-neuroscience-day

2026-01-29-emergences

Neurosciences and sparsity

2025-05-26-master-m-4-nc

2025-04-18-vibration-apparences

2025-03-11-phd-program-sparse-representations

NeuroSchool PhD Program in Neuroscience: Sparse representations

2025-02-11-neuromath

Kernel Heterogeneity Improves Sparseness of Natural Images Representations

Hugo Ladret, Christian Casanova, Laurent U Perrinet

2024-05-13-master-m-4-nc

Sparse representations

2024-04-10-ue-neurosciences-computationnelles

2024-04-17-phd-program-sparse-representations

2024-02-05-udem.md

2023-12-14-jraf.md

2023-12-01-biocomp.md

Emergences (2023 / 2027)

Beyond $\ell_1$ sparse coding in V1

Ilias Rentzeperis, Luca Calatroni, Laurent U Perrinet, Dario Prandi

2023-09-08_fresnel.md

2023-05-10-phd-program_neurosciences-computationnelles.md

Convolutional Sparse Coding is improved by heterogeneous uncertainty modeling

Hugo Ladret, Laurent U Perrinet

2023-04-05-ue-neurosciences-computationnelles

2023-04-03-master-m-4-nc

Detection of precise spiking motifs using spike-time dependent weight and delay plasticity

Antoine Grimaldi, Camille Besnainou, Hugo Ladret, Laurent U Perrinet

Pooling in a predictive model of V1 explains functional and structural diversity across species

Victor Boutin, Angelo Franciosini, Frédéric Chavane, Laurent U Perrinet

Which sparsity problem does the brain solve?

Ilias Rentzeperis, Luca Calatroni, Laurent U Perrinet, Dario Prandi

Statistics of the sparse representations of natural images

A Behavioral Receptive Field for Ocular Following in Monkeys: Spatial Summation and Its Spatial Frequency Tuning

Frédéric v Barthélemy, Jérome Fleuriet, Laurent U Perrinet, Guillaume S Masson

SDPC : A Sparse and Predictive Model of the Early Visual System

Angelo Franciosini

Soutenance de thèse Angelo Franciosini

Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system

Victor Boutin, Angelo Franciosini, Frédéric Chavane, Franck Ruffier, Laurent U Perrinet

ANR AgileNeuRobot (2021/2025)

Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding

Angelo Franciosini, Victor Boutin, Laurent U Perrinet

Understanding natural vision using deep predictive coding

PhD offer "Ultra-fast vision using Spiking Neural Networks"

Modelling Complex-cells and topological structure in the visual cortex of mammals using Sparse Predictive Coding

Angelo Franciosini, Victor Boutin, Laurent U Perrinet

2020-03-13: Soutenance de thèse Victor Boutin

Effect of top-down connections in Hierarchical Sparse Coding

Victor Boutin, Angelo Franciosini, Franck Ruffier, Laurent U Perrinet

Learning dynamics in a neural network model of the primary visual cortex

Hugo Ladret, Laurent U Perrinet

Postdoc position on Visual computations using Spatio-temporal Diffusion Kernels and Traveling Waves

Sparse Deep Predictive Coding captures contour integration capabilities of the early visual system

Victor Boutin, Angelo Franciosini, Frédéric Chavane, Franck Ruffier, Laurent U Perrinet

Speed-Selectivity in Retinal Ganglion Cells is Sharpened by Broad Spatial Frequency, Naturalistic Stimuli

Cesar U Ravello, Laurent U Perrinet, Maria-José Escobar, Adrián G Palacios

A hierarchical, multi-layer convolutional sparse coding algorithm based on predictive coding

Angelo Franciosini, Victor Boutin, Laurent U Perrinet

An adaptive homeostatic algorithm for the unsupervised learning of visual features

Laurent U Perrinet

Modelling Complex Cells of Early Visual Cortex using Predictive Coding

Angelo Franciosini, Victor Boutin, Laurent U Perrinet

Orientation selectivity to synthetic natural patterns in a cortical-like model of the cat primary visual cortex

Hugo Ladret, Nelson Cortes, Frédéric Chavane, Laurent U Perrinet, Christian Casanova

Sparse Deep Predictive Coding to model visual object recognition

Victor Boutin, Angelo Franciosini, Frédéric Chavane, Franck Ruffier, Laurent U Perrinet

Top-down connection in Hierarchical Sparse Coding

Victor Boutin, Angelo Franciosini, Franck Ruffier, Laurent U Perrinet

From biological vision to unsupervised hierarchical sparse coding

Victor Boutin, Angelo Franciosini, Franck Ruffier, Laurent U Perrinet

On the Origins of Hierarchy in Visual Processing

Angelo Franciosini, Laurent U Perrinet

Unsupervised Hierarchical Sparse Coding algorithm inspired by Biological Vision

Victor Boutin, Angelo Franciosini, Franck Ruffier, Laurent U Perrinet

Unsupervised learning applied to robotic vision

Tutorial: Sparse optimization in neural computations

Controlling an aerial robot with human gestures using bio-inspired algorithm

Victor Boutin, Angelo Franciosini, Franck Ruffier, Laurent U Perrinet

Efficient learning of sparse image representations using homeostatic regulation

Victor Boutin, Franck Ruffier, Laurent U Perrinet

Efficient learning of sparse image representations using homeostatic regulation

Victor Boutin, Franck Ruffier, Laurent U Perrinet

Differential response of the retinal neural code with respect to the sparseness of natural images

Cesar U Ravello, Maria-José Escobar, Adrián G Palacios, Laurent U Perrinet

Biologically-inspired characterization of sparseness in natural images

2016-10-26 : EUVIP BICV

Biologically-inspired characterization of sparseness in natural images

Laurent U Perrinet

ANR Horizontal-V1 (2017/2021)

DOC2AMU (2016/2019)

A dynamic model for decoding direction and orientation in macaque primary visual cortex

Wahiba Taouali, Giacomo Benvenuti, Frédéric Chavane, Laurent U Perrinet

A dynamic model for decoding direction and orientation in macaque primary visual cortex

Wahiba Taouali, Giacomo Benvenuti, Frédéric Chavane, Laurent U Perrinet

Push-Pull Receptive Field Organization and Synaptic Depression: Mechanisms for Reliably Encoding Naturalistic Stimuli in V1

Jens Kremkow, Laurent U Perrinet, Cyril Monier, Jose-Manuel Alonso, Ad M Aertsen, Yves Frégnac, Guillaume S Masson

Sparse Models for Computer Vision

Laurent U Perrinet

Sparse Coding Of Natural Images Using A Prior On Edge Co-Occurences

Laurent U Perrinet, James A Bednar

Edge co-occurrences can account for rapid categorization of natural versus animal images

Laurent U Perrinet, James A Bednar

Edge co-occurrences are sufficient to categorize natural versus animal images

Laurent U Perrinet, James A Bednar

Advances in Texture Analysis for Emphysema Classification

Rodrigo Nava, J Victor Marcos, Boris Escalante-Ramirez, Gabriel Cristóbal, Laurent U Perrinet, Raúl S J Estépar

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Demo 1, Task4: Implementation of models showing emergence of cortical fields and maps

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Edge statistics in natural images versus laboratory animal environments: implications for understanding lateral connectivity in V1

Laurent U Perrinet, David Fitzpatrick, James A Bednar

Phase space analysis of networks based on biologically realistic parameters

Nicole Voges, Laurent U Perrinet

Role of homeostasis in learning sparse representations

Laurent U Perrinet

Functional consequences of correlated excitatory and inhibitory conductances in cortical networks

Jens Kremkow, Laurent U Perrinet, Guillaume S Masson, Ad M Aertsen

Diffraction monochromatique, spectre audiographique

Phase space analysis of networks based on biologically realistic parameters

Nicole Voges, Laurent U Perrinet

Correlating Excitation and Inhibition in Visual Cortical Circuits : Functional Consequences and Biological Feasibility

Jens Oliver Kremkow

Modeling of spikes, sparseness and adaptation in the primary visual cortex: applications to imaging

Adaptive Sparse Spike Coding : applications of Neuroscience to the compression of natural images

Laurent U Perrinet

Control of the temporal interplay between excitation and inhibition by the statistics of visual input: a V1 network modelling study

Jens Kremkow, Laurent U Perrinet, Pierre Baudot, Manu Levy, Olivier Marre, Cyril Monier, Yves Frégnac, Guillaume S Masson, Ad M Aertsen

What adaptive code for efficient spiking representations? A model for the formation of receptive fields of simple cells

Laurent U Perrinet

Neural Codes for Adaptive Sparse Representations of Natural Images

Dynamical Neural Networks: modeling low-level vision at short latencies

Laurent U Perrinet

Manuel Samuelides

Self-Invertible 2D Log-Gabor Wavelets

Sylvain Fischer, Filip Šroubek, Laurent U Perrinet, Rafael Redondo, Gabriel Cristóbal

Neural Codes for Adaptive Sparse Representations of Natural Images

Laurent U Perrinet

On efficient sparse spike coding schemes for learning natural scenes in the primary visual cortex

Laurent U Perrinet

Sparse Approximation of Images Inspired from the Functional Architecture of the Primary Visual Areas

Sylvain Fischer, Rafael Redondo, Laurent U Perrinet, Gabriel Cristóbal

An efficiency razor for model selection and adaptation in the primary visual cortex

Laurent U Perrinet

Modeling of simple cells through a sparse overcomplete gabor wavelet representation based on local inhibition and facilitation

Rafael Redondo, Sylvain Fischer, Laurent U Perrinet, Gabriel Cristóbal

Sparse Gabor wavelets by local operations

Sylvain Fischer, Rafael Redondo, Laurent U Perrinet, Gabriel Cristóbal