Vincent Gripon
- Département Mathematical and Electrical Engineering (IMT Atlantique - MEE)
- Equipe Better Representations for Artificial Intelligence (Lab_STICC_BRAIn)
Présentation
Je suis Directeur de Recherche à IMT-Atlantique, une des meilleures grandes écoles Françaises. Je dirige également l'équipe BRAIN au sein du laboratoire CNRS Lab-STICC (UMR 6285), où ma recherche s'articule autour de l'intelligence artificielle, en particulier appliquée à des domaines tels que la vision et le traitement du langage naturel.
Domaines de recherche
Publications
Publications
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TENSLORA: TENSOR ALTERNATIVES FOR LOW-RANK ADAPTATION2026 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2026), May 2026, Barcelone, Spain |
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Réduction de la Résolution comme Technique de Compression pour les Systèmes d'Apprentissage Profond en VisionGRETSI2025, GRETSI, Aug 2025, Strasbourg, France |
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Input Resolution Downsizing as a Compression Technique for Vision Deep Learning Systems2025 International Joint Conference on Neural Networks (IJCNN), Jun 2025, Rome, Italy. pp.1-8, ⟨10.1109/IJCNN64981.2025.11229265⟩ |
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Bit-Width-Aware Design Environment for Few-Shot Learning on Edge AI HardwareIEEE International Symposium on Circuits and Systems (ISCAS 2025), May 2025, Londres, United Kingdom. pp.1-5, ⟨10.1109/ISCAS56072.2025.11044227⟩ |
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Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery DecodingEUSIPCO 2024: 32nd European Signal Processing Conference, Aug 2024, Lyon, France. ⟨10.23919/EUSIPCO63174.2024.10715003⟩ |
Design Environment of Quantization-Aware Edge AI Hardware for Few-Shot Learning2024 IEEE 67th International Midwest Symposium on Circuits and Systems (MWSCAS), Aug 2024, Springfield, France. pp.928-931, ⟨10.1109/MWSCAS60917.2024.10658789⟩ |
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On Transfer in Classification: How Well do Subsets of Classes Generalize?EUSIPCO 2024: 32nd European Signal Processing Conference, Aug 2024, Lyon, France. pp.1836-1840, ⟨10.23919/EUSIPCO63174.2024.10715243⟩ |
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Interpolation spatiale de signaux sur graphes avec une application pour la fusion d'ensembles de données EEG de diverses dimensionsGRETSI : 29ème colloque du Groupement de Recherche en Traitement du Signal et des Images, 2023, Grenoble, France |
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Inter-Operability of Compression Techniques for Efficient Deployment of CNNs on MicrocontrollersSYSINT 2022: International Conference on System-Integrated Intelligence, Sep 2022, Genova, Italy. pp.543-552, ⟨10.1007/978-3-031-16281-7_51⟩ |
Entropy Based Feature Regularization to Improve Transferability of Deep Learning ModelsICASSP 2023: IEEE International Conference on Acoustics, Speech and Signal Processing, Jun 2023, Rhodes Island, Greece. pp.1-5, ⟨10.1109/ICASSP49357.2023.10095195⟩ |
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Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPUSYSINT 2022: International Conference on System-Integrated Intelligence, Springer, Sep 2022, Genova, Italy. pp.553-563, ⟨10.1007/978-3-031-16281-7_52⟩ |
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Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various DimensionalitiesICASSP 2023: IEEE International Conference on Acoustics, Speech and Signal Processing, Jun 2023, Rhodes Island, Greece. pp.1-5, ⟨10.1109/ICASSP49357.2023.10097201⟩ |
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Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot ClassificationAISTATS 2023: 26th International Conference on Artificial Intelligence and Statistics, Apr 2023, Valence, Spain. pp.5899-5917 |
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Un modèle statistique pour prédire la généralisation dans des tâches de classification avec peu d'exemplesGRETSI : 29ème colloque du Groupement de Recherche en Traitement du Signal et des Images, 2023, Grenoble, France |
A Statistical Model for Predicting Generalization in Few-Shot ClassificationEUSIPCO 2023: 31st European Signal Processing Conference, Sep 2023, Helsinki, Finland. pp.1260-1264, ⟨10.23919/EUSIPCO58844.2023.10289951⟩ |
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Active Learning for Efficient Few-Shot ClassificationICASSP 2023: IEEE International Conference on Acoustics, Speech and Signal Processing, Jun 2023, Rhodes Island, Greece. pp.1-5, ⟨10.1109/ICASSP49357.2023.10095220⟩ |
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Régularisation entropique des vecteurs de caractéristiques d'un réseau de neurones pour une meilleur transférabilitéGRETSI 2023 : XXIXème Colloque Francophone de Traitement du Signal et des Images, Groupe de Recherche et d'Etudes de Traitement du Signal et des Images GRETSI, Aug 2023, Grenoble (FRANCE), France |
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Interpolation spatiale de signaux sur graphes avec une application pour la fusion d'ensembles de données EEG de diverses dimensionsGRETSI'23: XXIXème Colloque Francophone de Traitement du Signal et des Images, Aug 2023, Grenoble, France |
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Investigating the Not-So-Obvious Effects of Structured PruningICML 2022 - Hardware-aware efficient training (HAET), Jul 2022, Baltimore, United States |
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A Local Mixup to Prevent Manifold IntrusionEUSIPCO 2022: 30th European Signal Processing Conference, Aug 2022, Belgrade, Serbia. ⟨10.23919/EUSIPCO55093.2022.9909890⟩ |
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Leveraging Structured Pruning of Convolutional Neural NetworksSiPS 2022: IEEE Workshop on Signal Processing Systems, Nov 2022, Rennes, France. pp.1-6, ⟨10.1109/SiPS55645.2022.9919253⟩ |
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Un Mixup Local pour empêcher les intrusions de variétésGRETSI 2022 : 28ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2022, Nancy, France |
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Élagage de réseaux profond de neurones par dégradation sélective des pondérationsGRETSI 2022 : 28ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2022, Nancy, France |
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Le manchot, la banane et la bibliothèque. . . (de la désambiguïsation d'une tâche de classification avec un exemple)GRETSI 2022 : 28ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2022, Nancy, France |
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Pruning Graph Convolutional Networks to Select Meaningful Graph Frequencies for FMRI DecodingEUSIPCO 2022: 30th European Signal Processing Conference, Aug 2022, Belgrade, Serbia. pp.937-941, ⟨10.23919/EUSIPCO55093.2022.9909966⟩ |
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Élagage de réseaux de neurones convolutifs sur graphes pour la sélection de fréquences significatives pour le décodage d'IRMfGRETSI 2022 : 28ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2022, Nancy, France |
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Classes adversaires dans l'apprentissage avec peu d'exemplesGRETSI 2022 : 28ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2022, Nancy, France |
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Using Deep Neural Networks to Predict and Improve the Performance of Polar CodesISTC 2021: 11th IEEE International Symposium on Topics in Coding, Aug 2021, Montréal, Canada. ⟨10.1109/ISTC49272.2021.9594059⟩ |
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Graph Topology Inference Benchmarks for Machine LearningMLSP 2020 : IEEE 30th International Workshop on Machine Learning for Signal Processing, Sep 2020, Espoo, Brazil. pp.1-6, ⟨10.1109/MLSP49062.2020.9231794⟩ |
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Graph-based Interpolation of Feature Vectors for Accurate Few-Shot ClassificationICPR 2020: 25th International Conference on Pattern Recognition, Jan 2021, Milan, Italy. pp.8164-8171, ⟨10.1109/ICPR48806.2021.9412076⟩ |
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Leveraging the Feature Distribution in Transfer-Based Few-Shot LearningICANN 2021: 30th International Conference on Artificial Neural Networks, Sep 2021, Bratislava, Slovakia. pp.487-499, ⟨10.1007/978-3-030-86340-1_39⟩ |
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Towards an Intrinsic Definition of Robustness for a ClassifierICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2021, Toronto, Canada. pp.4015-4019, ⟨10.1109/ICASSP39728.2021.9414573⟩ |
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Attention Based Pruning for Shift NetworksICPR 2020: 25th International Conference on Pattern Recognition, Jan 2021, Milan (virtual), Italy. pp.4054-4061, ⟨10.1109/ICPR48806.2021.9412859⟩ |
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Inferring Graph Signal Translations as Invariant Transformations for Classification TasksEUSIPCO 2021: 29th European Signal Processing Conference, Aug 2021, Dublin, Ireland. ⟨10.23919/EUSIPCO54536.2021.9616010⟩ |
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Improving Classification Accuracy With Graph FilteringICIP 2021: IEEE International Conference on Image Processing, Sep 2021, Anchorage, United States. pp.334-338, ⟨10.1109/ICIP42928.2021.9506042⟩ |
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Few-Shot Decoding of Brain Activation MapsEUSIPCO 2021: 29th European Signal Processing Conference, Aug 2021, Dublin, Ireland. pp.1326-1330, ⟨10.23919/EUSIPCO54536.2021.9616158⟩ |
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Efficient Hardware Implementation of Incremental Learning and Inference on ChipNEWCAS 2019 : 17th IEEE International New Circuits and Systems Conference, Jun 2019, Munich, Germany. ⟨10.1109/NEWCAS44328.2019.8961310⟩ |
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Robustesse structurelle des architectures d'apprentissage profondGRETSI, Aug 2020, Lille, France |
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GPU-based Self-Organizing-Maps for Post-Labeled Few-Shot Unsupervised LearningInternational Conference on Neural Information Processing (ICONIP) 2020, Aug 2020, Bangkok, Thailand. pp.404-416, ⟨10.1007/978-3-030-63833-7_34⟩ |
Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural NetworksNEWCAS 2020 : 18th IEEE International New Circuits and Systems Conference, Jun 2020, Montréal, Canada. pp.206-209, ⟨10.1109/NEWCAS49341.2020.9159769⟩ |
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Un modèle unifié pour la classification de signaux sur graphe avec de l'apprentissage profondGRETSI, Aug 2020, Lille, France |
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Deep Geometric Knowledge Distillation with GraphsICASSP 2020: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2020, Barcelona, Spain. pp.8484-8488, ⟨10.1109/ICASSP40776.2020.9053986⟩ |
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Introducing Graph Smoothness Loss for Training Deep Learning Architectures2019 IEEE Data Science Workshop (DSW), Jun 2019, Minneapolis, United States. pp.160-164, ⟨10.1109/DSW.2019.8755559⟩ |
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Structural Robustness for Deep Learning Architectures2019 IEEE Data Science Workshop (DSW), Jun 2019, Minneapolis, United States. pp.125-129, ⟨10.1109/DSW.2019.8755564⟩ |
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Comparing linear structure-based and data-driven latent spatial representations for sequence predictionSPIE Optical Engineering + Applications, Aug 2019, San Diego, United States. ⟨10.1117/12.2528450⟩ |
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Robustesse des réseaux de neurones profonds aux défaillances mémoireGRETSI, Aug 2019, Lille, France |
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Training Modern Deep Neural Networks for Memory-Fault Robustness2019 IEEE International Symposium on Circuits and Systems (ISCAS), May 2019, Sapporo, Japan. pp.1-5, ⟨10.1109/ISCAS.2019.8702382⟩ |
An Inside Look at Deep Neural Networks using Graph Signal Processing2018 Information Theory and Applications Workshop (ITA), Feb 2018, San Diego, CA, United States. pp.1-9, ⟨10.1109/ITA.2018.8503214⟩ |
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Improving Accuracy of Nonparametric Transfer Learning Via Vector SegmentationICASSP 2018 : IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, France. ⟨10.1109/ICASSP.2018.8462273⟩ |
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Matching Convolutional Neural Networks without Priors about DataDSW 2018 : IEEE Data Science Workshop, Jun 2018, Lausanne, France. ⟨10.1109/DSW.2018.8439900⟩ |
Graph-Projected Signal ProcessingGlobalSIP 2018 : IEEE International Conference on Signal and Information Processing, Nov 2018, Anaheim, États-Unis. ⟨10.1109/GlobalSIP.2018.8646674⟩ |
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Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative MemoriesSIPS 2017 : IEEE International Workshop on Signal Processing Systems, Oct 2017, Lorient, France. pp.1 - 4, ⟨10.1109/SiPS.2017.8109978⟩ |
An Intrinsic Difference Between Vanilla RNNs and GRU ModelsCOGNITIVE 2017 : Ninth International Conference on Advanced Cognitive Technologies and Applications, Feb 2017, Athènes, Greece. pp.76 - 81 |
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Incremental Learning on ChipGlobalSIP 2017 : 5th IEEE Global Conference on Signal and Information Processing, Nov 2017, Montréal, Canada. ⟨10.1109/GlobalSIP.2017.8309068⟩ |
Translation sur graphe avec préservation du voisinageGRETSI 2017 : 26ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2017, Juan Les Pins, France |
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Evaluating Graph Signal Processing for Neuroimaging Through Classification and Dimensionality ReductionGlobalSIP 2017 : 5th IEEE Global Conference on Signal and Information Processing, Nov 2017, Montreal, Canada. pp.618 - 622, ⟨10.1109/GlobalSIP.2017.8309033⟩ |
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Learning local receptive fields and their weight sharing scheme on graphs2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Nov 2017, Montreal, France. ⟨10.1109/GlobalSIP.2017.8309034⟩ |
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Tropical graph signal processing2017 51st Asilomar Conference on Signals, Systems, and Computers, Oct 2017, Pacific Grove, France. ⟨10.1109/ACSSC.2017.8335134⟩ |
Performance of Neural Clique Networks Subject to Synaptic NoiseCOGNITIVE 2017 : The Ninth International Conference on Advanced Cognitive Technologies and Applications, Feb 2017, Athènes, Greece. pp.4 - 9 |
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NoC-MRAM Architecture for Memory-Based Computing: database-search case studyNEWCAS 2017 : 15th IEEE International New Circuits and Systems Conference, Jun 2017, Strasbourg, France. ⟨10.1109/NEWCAS.2017.8010167⟩ |
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Finding All Matches in a Database using Binary Neural NetworksCOGNITIVE 2017: The Ninth International Conference on Advanced Cognitive Technologies and Applications, Feb 2017, Athènes, Greece. pp.59-64 |
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Improved Willshaw Networks with Local InhibitionThe Eighth International Conference on Advanced Cognitive Technologies and Applications, Mar 2016, Rome, Italy |
Distributed coding and synaptic pruningISTC 2016 : 9th International symposium on Turbo Codes and Iterative Information Processing, Sep 2016, Brest, France. pp.206 - 210 |
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Neighborhood-Preserving Translations on GraphsGlobalSIP 2016 : IEEE Global Conference on Signal and Information Processing, Dec 2016, Arlington, United States. pp.410 - 414 |
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A Neural Network Model for Solving the Feature Correspondence ProblemICANN 2016 : 25th International Conference on Artificial Neural Networks, Sep 2016, Barcelone, Spain. pp.439 - 446, ⟨10.1007/978-3-319-44781-0_52⟩ |
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A Turbo-Inspired Iterative Approach for Correspondence Problems of Image FeaturesISTC 2016 : 9th International symposium on Turbo Codes and Iterative Information Processing, Sep 2016, Brest, France. pp.226 - 230, ⟨10.1109/ISTC.2016.7593110⟩ |
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Assembly output codes for learning neural networksISTC 2016 - 9th International Symposium on Turbo Codes & Iterative Information Processing, Sep 2016, Brest, France. pp.285-289, ⟨10.1109/ISTC.2016.7593122⟩ |
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Towards a characterization of the Uncertainty cuve for graphsICASSP 2016 : 41st IEEE International Conference on Acoustics, Speech and Signal Processing, Mar 2016, Shanghai, China. pp.4558 - 4562, ⟨10.1109/ICASSP.2016.7472540⟩ |
Nearest Neighbour Search Using Binary Neural NetworksIJCNN 2016 : International Joint Conference on Neural Networks , Jul 2016, Vancouver, Canada. pp.5106 - 5112, ⟨10.1109/IJCNN.2016.7727873⟩ |
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Massively parallel implementation of sparse message retrieval algorithms in Clustered Clique NetworksThe 2016 International Conference on High Performance Computing & Simulation (HPCS2016), Jul 2016, Innsbrück, Austria. pp.935 - 939, ⟨10.1109/HPCSim.2016.7568434⟩ |
Characterizing graphs from diffused worshopGSP 2016 : Graph Signal Processing Workshop, May 2016, Philadelphia, United States |
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Compression of Deep Neural Networks on the FlyICANN 2016 : 25th International Conference on Artificial Neural Networks, Sep 2016, Barcelone, Spain. pp.153 - 160 |
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Algorithm and Implementation of an Associative Memory for Oriented Edge Detection Using Improved Clustered Neural Networks2015 International Symposium on Circuits and Systems (ISCAS 2015), May 2015, Lisbonne, Portugal. pp.2501 - 2504, ⟨10.1109/ISCAS.2015.7169193⟩ |
A novel algorithm for measuring graph similarity: application to brain networks7th Annual International IEEE EMBS Conference on Neural Engineering (NER), Apr 2015, Montpellier, France. pp.1068--1071 |
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Using Tags to Improve Diversity of Sparse Associative MemoriesCOGNITIVE 2015: The Seventh International Conference on Advanced Cognitive Technologies and Applications, Mar 2015, Nice, France. pp.1 - 7 |
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SimNet: A new algorithm for measuring brain networks similarityICABME 2015 : 3rd International Conference on Advances in Biomedical Engineering Advances in Biomedical Engineering, Sep 2015, Beyrouth, Lebanon. pp.119 - 122, ⟨10.1109/ICABME.2015.7323266⟩ |
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Automatic face recognition using SIFT and networks of tagged neural cliquesInternational Conference on Advanced Cognitive Technologies and Applications 2015, Mar 2015, Nice, France. pp.57 - 61 |
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Vers une caractérisation de la courbe d'incertitude pour des graphes portant des signauxGRETSI 2015 : 25ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2015, Lyon, France. pp.1 - 5 |
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Graph reconstruction from the observation of diffused signalsAllerton 2015 : 63th Annual Allerton conference on communication, control and Computing, Sep 2015, Allerton, United States. pp.1 - 5 |
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Implementing Relational-Algebraic Operators for Improving Cognitive Abilities in Networks of Neural CliquesCOGNITIVE 2015 : the 7th International Conference on Advanced Cognitive Technologies and Applications, Mar 2015, Nice, France. pp.36 - 41 |
Restricted Clustered Neural Network for Storing Real Datathe 25th edition, May 2015, Pittsburgh, France. pp.205-210, ⟨10.1145/2742060.2743767⟩ |
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Toward An Uncertainty Principle For Weighted GraphsEUSIPCO 2015 : 23rd European Signal Processing Conference, Aug 2015, Nice, France. pp.1496 - 1500, ⟨10.1109/EUSIPCO.2015.7362633⟩ |
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A model of bottom-up visual attention using cortical magnificationICASSP 2015 : the 40th IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2015, Brisbane, Australia. pp.1493 - 1497 |
Algorithm and implementation of an associative memory for oriented edge detection using improved clustered neural networks2015 IEEE International Symposium on Circuits and Systems (ISCAS), May 2015, Lisbon, France. pp.2501-2504, ⟨10.1109/ISCAS.2015.7169193⟩ |
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Neural Associative Memories as Accelerators for Binary Vector SearchCOGNITIVE 2015 : 7th International Conference on Advanced Cognitive Technologies and Applications, Mar 2015, Nice, France. pp.85 - 89 |
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Towards a Spectral Characterization of Signals Supported on Small-World NetworksICASSP 2014 : IEEE International Conferences on Acoustics, Speech and Signal Processing, May 2014, Florence, Italy. pp.4793-4797, ⟨10.1109/ICASSP.2014.6854512⟩ |
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Algorithm and Architecture for a Multiple-Field Context-Driven Search Engine Using Fully-Parallel Clustered Associative MemoriesSiPS 2014 : IEEE International Workshop on Signal Processing Systems, Oct 2014, Belfast, United Kingdom. pp.1 - 6, ⟨10.1109/SiPS.2014.6986075⟩ |
Sparse Binary Matrices as Efficient Associative MemoriesAllerton 2014 : 52nd Annual Conference on Communication, Control, and Computing, Oct 2014, Monticello, United States. pp.499 - 504, ⟨10.1109/ALLERTON.2014.7028496⟩ |
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A GPU-based Associative Memory using Sparse Neural NetworksHPCS 2014 : the international conference on High Performance Computing and Simulation, Jul 2014, Bologna, Italy. pp.688 - 692, ⟨10.1109/HPCSim.2014.6903755⟩ |
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A study of retrieval algorithms of sparse messages in networks of neural cliquesCOGNITIVE 2014: 6th International Conference on Advanced Cognitive Technologies and Applications, May 2014, Venise, Italy. pp.140-146 |
Huffman Coding for Storing Non-uniformly Distributed Messages in Networks of Neural CliquesAAAI 2014 : the 28th Conference on Artificial Intelligence, Jul 2014, Québec, Canada. pp.262-268 |
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Information, Noise, Coding, Modulation: What about the Brain?ISTC 2014 : 8th International Symposium on Turbo Codes and Iterative Information Processing, Aug 2014, Brême, Germany. pp.167 - 172, ⟨10.1109/ISTC.2014.6955107⟩ |
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Cluster-based Associative Memories Built From Unreliable StorageICASSP 2014 : IEEE International Conferences on Acoustics, Speech and Signal Processing, May 2014, Florence, Italy. pp.8370-8374, ⟨10.1109/ICASSP.2014.6855234⟩ |
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Maximum Likelihood Associative MemoriesITW 2013 : IEEE Information Theory Workshop, Sep 2013, Seville, Spain. pp.1 - 5 |
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A mental information theoryFrench-Israeli Inter-Academic Meeting on Mathematics, May 2013, Paris, France |
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Sparse Structured Associative Memories As Efficient Set-Membership Data StructuresAllerton 2013 : 51st annual Allerton Conference on Communication, Control, and Computing, Oct 2013, Allerton, United States. pp.500 - 505 |
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Mémoires associatives pour observations flouesGRETSI 2013 : 24ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2013, Brest, France |
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A Low-Power Content-Adressable-Memory Based on Clustered-Sparse-NetworksASAP 2013 : 24th IEEE International Conference on Application-specific Systems, Architectures and Processors, Jun 2013, Washington, United States |
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Reconstructing a Graph from Path TracesISIT 2013 : proceedings of the IEEE International Symposium on Information Theory, Jul 2013, Istanbul, Turkey |
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Codes sur graphes et mémoire cérébraleGRETSI 2013 : 24ème colloque du Groupement de Recherche en Traitement du Signal, Sep 2013, Brest, France |
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Reduced-complexity binary-weight-coded associative memoriesICASSP 2013 : the 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2013, Vancouver, Canada |
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Learning long sequences in binary neural networksCognitive 2012 : 4th International Conference on Advanced Cognitive Technologies and Applications, Jul 2012, Nice, France. pp.165 - 170 |
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Random clique codesISTC 2012 : 7th International Symposium on Turbo Codes and Iterative Information Processing, Aug 2012, Gothenburg, Suède. pp.121-125, ⟨10.1109/ISTC.2012.6325211⟩ |
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Compressing multisets using triesITW 2012 : IEEE Information Theory Workshop, Sep 2012, Lausanne, Switzerland. pp.642-646, ⟨10.1109/ITW.2012.6404756⟩ |
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Architecture and Implementation of an Associative Memory Using Sparse Clustered NetworksISCAS 2012 : IEEE International Symposium on Circuits and Systems, May 2012, Seoul, South Korea. pp.2901-2904, ⟨10.1109/ISCAS.2012.6271922⟩ |
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Nearly-optimal associative memories based on distributed constant weight codesITA 2012 : Information Theory and Applications Workshop, Sep 2012, Lausanne, Switzerland. pp.269 - 273, ⟨10.1109/ITA.2012.6181790⟩ |
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A simple and efficient way to store many messages using neural cliquesCCMB 2011: IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain, May 2011, Paris, France |
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Coded hopfield networks6th International Symposium on Turbo codes, Sep 2010, Brest, France. pp.1 - 5, ⟨10.1109/ISTC.2010.5613860⟩ |
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Qualitative Concurrent Stochastic Games with Imperfect InformationAutomata, Languages and Programming, 36th International Colloquium, ICALP 2009, Jul 2009, Rhodes, Greece. pp.200-211 |
Réseaux de clusters de neurones restreintsGRETSI 2015 : 25ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2015, Lyon, France. pp.1 - 5 |
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Algorithm and Implementation of an Associative Memory for Oriented Edge Detection Using Improved Clustered Neural NetworksInternational Workshop on Neuromorphic and Brain-Based Computing Systems (Neucomp), Mar 2015, Grenoble, France |
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Impact du bruit synaptique sur les performances des réseaux de cliques neuralesGRETSI 2015 : 25ème colloque du Groupement de Recherche en Traitement du Signal et des Images, Sep 2015, Lyon, France. pp.1 - 5 |
Petite mathématique du cerveauOdile Jacob, pp.160, 2012, Sciences, 978-2-7381-2838-6 |
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Graphs as Tools to Improve Deep Learning MethodsAdvances in Artificial Intelligence: Reviews, 2, International Frequency Sensor Association (IFSA) Publishing, In press |
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Transfer Learning with Sparse Associative MemoriesTheoretical Neural Computation, pp.497-512, 2019, ⟨10.1007/978-3-030-30487-4_39⟩ |
Uncertainty principle on graphsVertex-Frequency Analysis of Graph Signals, pp.317-340, 2019, Signals and Communication Technology book series (SCT), ⟨10.1007/978-3-030-03574-7_9⟩ |
Compression par régularisation sélective de réseaux de neurones pour la conduite autonomeFrance, N° de brevet: FR3114420. 2022 |
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Compression par régularisation sélective de réseaux de neurones pour la conduite autonomeFrance, N° de brevet: FR3113272. 2022 |
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Compression automatisée de réseaux de neurones pour la conduite autonomeFrance, Patent n° : FR3113273. 2022 |
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Dispositif d'apprentissage et de décodage de messages, mettant en œuvre un réseau de neurones, procédés d'apprentissage et de décodage et programmes d'ordinateur correspondantsFrance, N° de brevet: WO2012025583. DI-TBN-10-003. 2012 |
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Games with imperfect information.2008 |
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MONET: Modeling and Optimization of neural NEtwork Training from Edge to Data Centers IEEE Publication2026 |
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Few and Fewer: Learning better from few examples using fewer base classes2024 |
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A Unified Deep Learning Formalism For Processing Graph Signals2020 |
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BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization2020 |
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Attention Based Pruning for Shift Networks2019 |
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Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks2018 |
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Tropical Graph Signal Processing2017 |
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Networks of Neural CliquesNeural and Evolutionary Computing [cs.NE]. Télécom Bretagne, 2011. English. ⟨NNT : ⟩ |
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Efficient Representations for Graph and Neural Network SignalsMachine Learning [cs.LG]. ENS Lyon, 2020 |