Qualitative Concurrent Stochastic Games with Imperfect Information. - Vincent Gripon; Olivier Serre (ICALP (2), 2009)

Qualitative Concurrent Games with Imperfect Information - Vincent Gripon; Olivier Serre (CoRR, 2009)

A simple and efficient way to store many messages using neural cliques. - Vincent Gripon; Claude Berrou (CCMB, 2011)

Sparse Neural Networks With Large Learning Diversity. - Vincent Gripon; Claude Berrou (IEEE Trans. Neural Networks, 2011)

Networks of Neural Cliques. (Réseaux de cliques neurales). - Vincent Gripon (2011)

Architecture and implementation of an associative memory using sparse clustered networks. - Hooman Jarollahi; Naoya Onizawa; Vincent Gripon; Warren J. Gross (ISCAS, 2012)

Random clique codes. - Vincent Gripon; Vitaly Skachek; Warren J. Gross; Michael G. Rabbat (ISTC, 2012)

Nearly-optimal associative memories based on distributed constant weight codes. - Vincent Gripon; Claude Berrou (ITA, 2012)

Compressing multisets using tries. - Vincent Gripon; Michael G. Rabbat; Vitaly Skachek; Warren J. Gross (ITW, 2012)

Forwarding Without Repeating: Efficient Rumor Spreading in Bounded-Degree Graphs - Vincent Gripon; Vitaly Skachek; Michael G. Rabbat (CoRR, 2012)

Learning sparse messages in networks of neural cliques - Behrooz Kamary Aliabadi; Claude Berrou; Vincent Gripon; Xiaoran Jiang (CoRR, 2012)

Sparse structured associative memories as efficient set-membership data structures. - Vincent Gripon; Vitaly Skachek; Michael G. Rabbat (Allerton, 2013)

A low-power Content-Addressable Memory based on clustered-sparse networks. - Hooman Jarollahi; Vincent Gripon; Naoya Onizawa; Warren J. Gross (ASAP, 2013)

Reduced-complexity binary-weight-coded associative memories. - Hooman Jarollahi; Naoya Onizawa; Vincent Gripon; Warren J. Gross (ICASSP, 2013)

Reconstructing a graph from path traces. - Vincent Gripon; Michael G. Rabbat (ISIT, 2013)

Maximum likelihood associative memories. - Vincent Gripon; Michael G. Rabbat (ITW, 2013)

A study of retrieval algorithms of sparse messages in networks of neural cliques. - Ala Aboudib; Vincent Gripon; Xiaoran Jiang (CoRR, 2013)

Storing non-uniformly distributed messages in networks of neural cliques. - Bartosz Boguslawski; Vincent Gripon; Fabrice Seguin; Frédéric Heitzmann (CoRR, 2013)

Improving Sparse Associative Memories by Escaping from Bogus Fixed Points. - Zhe Yao; Vincent Gripon; Michael G. Rabbat (CoRR, 2013)

Bounds on associative memories - Vincent Gripon; Michael G. Rabbat (CoRR, 2013)

A Massively Parallel Associative Memory Based on Sparse Neural Networks - Zhe Yao; Vincent Gripon; Michael G. Rabbat (CoRR, 2013)

Huffman Coding for Storing Non-Uniformly Distributed Messages in Networks of Neural Cliques. - Bartosz Boguslawski; Vincent Gripon; Fabrice Seguin; Frédéric Heitzmann (AAAI, 2014)

Sparse binary matrices as efficient associative memories. - Vincent Gripon; Vitaly Skachek; Michael G. Rabbat (Allerton, 2014)

A GPU-based associative memory using sparse Neural Networks. - Zhe Yao; Vincent Gripon; Michael G. Rabbat (HPCS, 2014)

Cluster-based associative memories built from unreliable storage. - François Leduc-Primeau; Vincent Gripon; Michael G. Rabbat; Warren J. Gross (ICASSP, 2014)

Towards a spectral characterization of signals supported on small-world networks. - Michael G. Rabbat; Vincent Gripon (ICASSP, 2014)

Information, noise, coding, modulation: What about the brain? - Claude Berrou; Olivier Dufor; Vincent Gripon; Xiaoran Jiang (ISTC, 2014)

Algorithm and architecture for a multiple-field context-driven search engine using fully-parallel clustered associative memories. - Hooman Jarollahi; Naoya Onizawa; Vincent Gripon; Takahiro Hanyu; Warren J. Gross (SiPS, 2014)

Combating Corrupt Messages in Sparse Clustered Associative Memories. - Zhe Yao; Vincent Gripon; Michael G. Rabbat (CoRR, 2014)

A Nonvolatile Associative Memory-Based Context-Driven Search Engine Using 90 nm CMOS/MTJ-Hybrid Logic-in-Memory Architecture. - Hooman Jarollahi; Naoya Onizawa; Vincent Gripon; Noboru Sakimura; Tadahiko Sugibayashi; Tetsuo Endoh; Hideo Ohno; Takahiro Hanyu; Warren J. Gross (IEEE J. Emerg. Sel. Topics Circuits Syst., 2014)

Algorithm and Architecture of Fully-Parallel Associative Memories Based on Sparse Clustered Networks. - Hooman Jarollahi; Naoya Onizawa; Vincent Gripon; Warren J. Gross (J. Signal Process. Syst., 2014)

Graph reconstruction from the observation of diffused signals. - Bastien Pasdeloup; Michael G. Rabbat; Vincent Gripon; Dominique Pastor; Grégoire Mercier (Allerton, 2015)

Toward an uncertainty principle for weighted graphs. - Bastien Pasdeloup; Réda Alami; Vincent Gripon; Michael G. Rabbat (EUSIPCO, 2015)

Restricted Clustered Neural Network for Storing Real Data. - Robin Danilo; Philippe Coussy; Laura Conde-Canencia; Vincent Gripon; Warren J. Gross (ACM Great Lakes Symposium on VLSI, 2015)

A model of bottom-up visual attention using cortical magnification. - Ala Aboudib; Vincent Gripon; Gilles Coppin (ICASSP, 2015)

Algorithm and implementation of an associative memory for oriented edge detection using improved clustered neural networks. - Robin Danilo; Hooman Jarollahi; Vincent Gripon; Philippe Coussy; Laura Conde-Canencia; Warren J. Gross (ISCAS, 2015)

A novel algorithm for measuring graph similarity: Application to brain networks. - Ahmad Mheich; Mahmoud Hassan; Vincent Gripon; Mohamad Khalil; Claude Berrou; Olivier Dufor; Fabrice Wendling (NER, 2015)

Algorithm and Architecture for a Low-Power Content-Addressable Memory Based on Sparse Clustered Networks. - Hooman Jarollahi; Vincent Gripon; Naoya Onizawa; Warren J. Gross (IEEE Trans. Very Large Scale Integr. Syst., 2015)

Associative Memory based on clustered Neural Networks: Improved model and architecture for Oriented Edge Detection. - Robin Danilo; Hugues Nono Wouafo; Cyrille Chavet; Vincent Gripon; Laura Conde-Canencia; Philippe Coussy (DASIP, 2016)

Neighborhood-preserving translations on graphs. - Nicolas Grelier; Bastien Pasdeloup; Jean-Charles Vialatte; Vincent Gripon (GlobalSIP, 2016)

A Neural Network Model for Solving the Feature Correspondence Problem. - Ala Aboudib; Vincent Gripon; Gilles Coppin (ICANN (2), 2016)

Compression of Deep Neural Networks on the Fly. - Guillaume Soulié; Vincent Gripon; Maëlys Robert (ICANN (2), 2016)

Towards a characterization of the uncertainty curve for graphs. - Bastien Pasdeloup; Vincent Gripon; Grégoire Mercier; Dominique Pastor (ICASSP, 2016)

Massively parallel implementation of sparse message retrieval algorithms in Clustered Clique Networks. - Philippe Tigreat; Pierre-Henri Horrein; Vincent Gripon (HPCS, 2016)

Nearest Neighbour Search using binary neural networks. - Demetrio Ferro; Vincent Gripon; Xiaoran Jiang (IJCNN, 2016)

A turbo-inspired iterative approach for correspondence problems of image features. - Ala Aboudib; Vincent Gripon; Gilles Coppin (ISTC, 2016)

Distributed coding and synaptic pruning. - Eliott Coyac; Vincent Gripon; Charlotte Langlais; Claude Berrou (ISTC, 2016)

Assembly output codes for learning neural networks. - Philippe Tigreat; Carlos Eduardo Rosar Kós Lassance; Xiaoran Jiang; Vincent Gripon; Claude Berrou (ISTC, 2016)

A Biologically Inspired Framework for Visual Information Processing and an Application on Modeling Bottom-Up Visual Attention. - Ala Aboudib; Vincent Gripon; Gilles Coppin (Cogn. Comput., 2016)

Associative Memories to Accelerate Approximate Nearest Neighbor Search. - Vincent Gripon; Matthias Löwe; Franck Vermet (CoRR, 2016)

Characterization and inference of weighted graph topologies from observations of diffused signals. - Bastien Pasdeloup; Vincent Gripon; Grégoire Mercier; Dominique Pastor; Michael G. Rabbat (CoRR, 2016)

Generalizing the Convolution Operator to Extend CNNs to Irregular Domains. - Jean-Charles Vialatte; Vincent Gripon; Grégoire Mercier (CoRR, 2016)

Twin Neurons for Efficient Real-World Data Distribution in Networks of Neural Cliques: Applications in Power Management in Electronic Circuits. - Bartosz Boguslawski; Vincent Gripon; Fabrice Seguin; Frédéric Heitzmann (IEEE Trans. Neural Networks Learn. Syst., 2016)

Storing Sequences in Binary Tournament-Based Neural Networks. - Xiaoran Jiang; Vincent Gripon; Claude Berrou; Michael G. Rabbat (IEEE Trans. Neural Networks Learn. Syst., 2016)

Fault-Tolerant Associative Memories Based on c-Partite Graphs. - François Leduc-Primeau; Vincent Gripon; Michael G. Rabbat; Warren J. Gross (IEEE Trans. Signal Process., 2016)

Tropical graph signal processing. - Vincent Gripon (ACSSC, 2017)

Incremental learning on chip. - Ghouthi Boukli Hacene; Vincent Gripon; Nicolas Farrugia; Matthieu Arzel; Michel Jézéquel (GlobalSIP, 2017)

Evaluating graph signal processing for neuroimaging through classification and dimensionality reduction. - Mathilde Ménoret; Nicolas Farrugia; Bastien Pasdeloup; Vincent Gripon (GlobalSIP, 2017)

Learning local receptive fields and their weight sharing scheme on graphs. - Jean-Charles Vialatte; Vincent Gripon; Gilles Coppin (GlobalSIP, 2017)

NoC-MRAM architecture for memory-based computing: Database-search case study. - Mostafa Rizk; Jean-Philippe Diguet; Naoya Onizawa; Amer Baghdadi; Martha Johanna Sepúlveda; Y. Akgul; Vincent Gripon; Takahiro Hanyu (NEWCAS, 2017)

Translations on graphs with neighborhood preservation. - Bastien Pasdeloup; Vincent Gripon; Nicolas Grelier; Jean-Charles Vialatte; Dominique Pastor (CoRR, 2017)

Robust Associative Memories Naturally Occuring From Recurrent Hebbian Networks Under Noise. - Eliott Coyac; Vincent Gripon; Charlotte Langlais; Claude Berrou (CoRR, 2017)

Convolutional neural networks on irregular domains through approximate translations on inferred graphs. - Bastien Pasdeloup; Vincent Gripon; Jean-Charles Vialatte; Dominique Pastor (CoRR, 2017)

Matching Convolutional Neural Networks without Priors about Data. - Carlos Eduardo Rosar Kós Lassance; Jean-Charles Vialatte; Vincent Gripon (DSW, 2018)

Graph-Projected Signal Processing. - Nicolas Grelier; Carlos Eduardo Rosar Kós Lassance; Elsa Dupraz; Vincent Gripon (GlobalSIP, 2018)

Improving Accuracy of Nonparametric Transfer Learning Via Vector Segmentation. - Vincent Gripon; Ghouthi B. Hacene; Matthias Löwe; Franck Vermet (ICASSP, 2018)

An Inside Look at Deep Neural Networks Using Graph Signal Processing. - Vincent Gripon; Antonio Ortega; Benjamin Girault (ITA, 2018)

Laplacian Power Networks: Bounding Indicator Function Smoothness for Adversarial Defense. - Carlos Eduardo Rosar Kós Lassance; Vincent Gripon; Antonio Ortega (CoRR, 2018)

Transfer Incremental Learning using Data Augmentation. - Ghouthi Boukli Hacene; Vincent Gripon; Nicolas Farrugia; Matthieu Arzel; Michel Jézéquel (CoRR, 2018)

Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks. - Ghouthi Boukli Hacene; Vincent Gripon; Matthieu Arzel; Nicolas Farrugia; Yoshua Bengio (CoRR, 2018)

SimiNet: A Novel Method for Quantifying Brain Network Similarity. - Ahmad Mheich; Mahmoud Hassan; Mohamad Khalil; Vincent Gripon; Olivier Dufor; Fabrice Wendling (IEEE Trans. Pattern Anal. Mach. Intell., 2018)

Memory Vectors for Similarity Search in High-Dimensional Spaces. - Ahmet Iscen; Teddy Furon; Vincent Gripon; Michael G. Rabbat; Hervé Jégou (IEEE Trans. Big Data, 2018)

Characterization and Inference of Graph Diffusion Processes From Observations of Stationary Signals. - Bastien Pasdeloup; Vincent Gripon; Grégoire Mercier; Dominique Pastor; Michael G. Rabbat (IEEE Trans. Signal Inf. Process. over Networks, 2018)

Introducing Graph Smoothness Loss for Training Deep Learning Architectures. - Myriam Bontonou; Carlos Eduardo Rosar Kós Lassance; Ghouthi Boukli Hacene; Vincent Gripon; Jian Tang 005; Antonio Ortega (DSW, 2019)

Structural Robustness for Deep Learning Architectures. - Carlos Eduardo Rosar Kós Lassance; Vincent Gripon; Jian Tang 005; Antonio Ortega (DSW, 2019)

Transfer Learning with Sparse Associative Memories. - Quentin Jodelet; Vincent Gripon; Masafumi Hagiwara (ICANN (1), 2019)

Training Modern Deep Neural Networks for Memory-Fault Robustness. - Ghouthi Boukli Hacene; François Leduc-Primeau; Amal Ben Soussia; Vincent Gripon; François Gagnon (ISCAS, 2019)

Efficient Hardware Implementation of Incremental Learning and Inference on Chip. - Ghouthi B. Hacene; Vincent Gripon; Nicolas Farrugia; Matthieu Arzel; Michel Jézéquel (NEWCAS, 2019)

A Unified Deep Learning Formalism For Processing Graph Signals. - Myriam Bontonou; Carlos Eduardo Rosar Kós Lassance; Jean-Charles Vialatte; Vincent Gripon (CoRR, 2019)

Comparing linear structure-based and data-driven latent spatial representations for sequence prediction. - Myriam Bontonou; Carlos Eduardo Rosar Kós Lassance; Vincent Gripon; Nicolas Farrugia (CoRR, 2019)

Improved Visual Localization via Graph Smoothing. - Carlos Eduardo Rosar Kós Lassance; Yasir Latif; Ravi Garg; Vincent Gripon; Ian D. Reid 001 (CoRR, 2019)

Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative Memories. - Ghouthi Boukli Hacene; Vincent Gripon; Nicolas Farrugia; Matthieu Arzel; Michel Jézéquel (J. Signal Process. Syst., 2019)

Efficient Representations for Graph and Neural Network Signals. (Représentations efficaces pour les signaux sur graphes et réseaux de neurones). - Vincent Gripon (2020)

Deep Geometric Knowledge Distillation with Graphs. - Carlos Lassance; Myriam Bontonou; Ghouthi Boukli Hacene; Vincent Gripon; Jian Tang 005; Antonio Ortega (ICASSP, 2020)

GPU-Based Self-Organizing Maps for Post-labeled Few-Shot Unsupervised Learning. - Lyes Khacef; Vincent Gripon; Benoît Miramond (ICONIP (2), 2020)

Attention Based Pruning for Shift Networks. - Ghouthi Boukli Hacene; Carlos Lassance; Vincent Gripon; Matthieu Courbariaux; Yoshua Bengio (ICPR, 2020)

Graph-based Interpolation of Feature Vectors for Accurate Few-Shot Classification. - Yuqing Hu 001; Vincent Gripon; Stéphane Pateux (ICPR, 2020)

Graph Topology Inference Benchmarks for Machine Learning. - Carlos Lassance; Vincent Gripon; Gonzalo Mateos (MLSP, 2020)

Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks. - Ghouthi Boukli Hacene; Vincent Gripon; Matthieu Arzel; Nicolas Farrugia; Yoshua Bengio (NEWCAS, 2020)

Exploiting Unsupervised Inputs for Accurate Few-Shot Classification. - Yuqing Hu 001; Vincent Gripon; Stéphane Pateux (CoRR, 2020)

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. - Milos Nikolic 002; Ghouthi Boukli Hacene; Ciaran Bannon; Alberto Delmas Lascorz; Matthieu Courbariaux; Yoshua Bengio; Vincent Gripon; Andreas Moshovos (CoRR, 2020)

Predicting the Accuracy of a Few-Shot Classifier. - Myriam Bontonou; Louis Béthune; Vincent Gripon (CoRR, 2020)

ThriftyNets : Convolutional Neural Networks with Tiny Parameter Budget. - Guillaume Coiffier; Ghouthi Boukli Hacene; Vincent Gripon (CoRR, 2020)

Some Remarks on Replicated Simulated Annealing. - Vincent Gripon; Matthias Löwe; Franck Vermet (CoRR, 2020)

Few-shot Learning for Decoding Brain Signals. - Myriam Bontonou; Nicolas Farrugia; Vincent Gripon (CoRR, 2020)

Continuous Pruning of Deep Convolutional Networks Using Selective Weight Decay. - Hugo Tessier; Vincent Gripon; Mathieu Léonardon; Matthieu Arzel; Thomas Hannagan; David Bertrand (CoRR, 2020)

Ranking Deep Learning Generalization using Label Variation in Latent Geometry Graphs. - Carlos Lassance; Louis Béthune; Myriam Bontonou; Mounia Hamidouche; Vincent Gripon (CoRR, 2020)

DecisiveNets: Training Deep Associative Memories to Solve Complex Machine Learning Problems. - Vincent Gripon; Carlos Lassance; Ghouthi Boukli Hacene (CoRR, 2020)

Similarity between Base and Novel Classes: a Predictor of the Performance in Few-Shot Classification of Brain Activation Maps? - Myriam Bontonou; Nicolas Farrugia; Vincent Gripon (ACSCC, 2021)

Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (EUSIPCO, 2021)

Few-Shot Decoding of Brain Activation Maps. - Myriam Bontonou; Giulia Lioi; Nicolas Farrugia; Vincent Gripon (EUSIPCO, 2021)

Leveraging the Feature Distribution in Transfer-Based Few-Shot Learning. - Yuqing Hu 001; Vincent Gripon; Stéphane Pateux (ICANN (2), 2021)

Towards an Intrinsic Definition of Robustness for a Classifier. - Théo Giraudon; Vincent Gripon; Matthias Löwe; Franck Vermet (ICASSP, 2021)

Improving Classification Accuracy With Graph Filtering. - Mounia Hamidouche; Carlos Lassance; Yuqing Hu 001; Lucas Drumetz; Bastien Pasdeloup; Vincent Gripon (ICIP, 2021)

Using Deep Neural Networks to Predict and Improve the Performance of Polar Codes. - Mathieu Léonardon; Vincent Gripon (ISTC, 2021)

Representing Deep Neural Networks Latent Space Geometries with Graphs. - Carlos Lassance; Vincent Gripon; Antonio Ortega (Algorithms, 2021)

Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification. - Myriam Bontonou; Nicolas Farrugia; Vincent Gripon (CoRR, 2021)

Graphs as Tools to Improve Deep Learning Methods. - Carlos Lassance; Myriam Bontonou; Mounia Hamidouche; Bastien Pasdeloup; Lucas Drumetz; Vincent Gripon (CoRR, 2021)

Predicting the Generalization Ability of a Few-Shot Classifier. - Myriam Bontonou; Louis Béthune; Vincent Gripon (Inf., 2021)

Improved Visual Localization via Graph Filtering. - Carlos Lassance; Yasir Latif; Ravi Garg; Vincent Gripon; Ian Reid 001 (J. Imaging, 2021)

Quantization and Deployment of Deep Neural Networks on Microcontrollers. - Pierre-Emmanuel Novac; Ghouthi Boukli Hacene; Alain Pegatoquet; Benoît Miramond; Vincent Gripon (Sensors, 2021)

A Local Mixup to Prevent Manifold Intrusion. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (EUSIPCO, 2022)

Pruning Graph Convolutional Networks to Select Meaningful Graph Frequencies for FMRI Decoding. - Yassine El Ouahidi; Hugo Tessier; Giulia Lioi; Nicolas Farrugia; Bastien Pasdeloup; Vincent Gripon (EUSIPCO, 2022)

Leveraging Structured Pruning of Convolutional Neural Networks. - Hugo Tessier; Vincent Gripon; Mathieu Léonardon; Matthieu Arzel; David Bertrand; Thomas Hannagan (SiPS, 2022)

Energy Consumption Analysis of Pruned Semantic Segmentation Networks on an Embedded GPU. - Hugo Tessier; Vincent Gripon; Mathieu Léonardon; Matthieu Arzel; David Bertrand; Thomas Hannagan (SYSINT, 2022)

Inter-Operability of Compression Techniques for Efficient Deployment of CNNs on Microcontrollers. - Hamoud Younes; Hugo Le Blevec; Mathieu Léonardon; Vincent Gripon (SYSINT, 2022)

Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning. - Yuqing Hu 001; Stéphane Pateux; Vincent Gripon (Algorithms, 2022)

Preventing Manifold Intrusion with Locality: Local Mixup. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (CoRR, 2022)

EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. - Yassir Bendou; Yuqing Hu 001; Raphaël Lafargue; Giulia Lioi; Bastien Pasdeloup; Stéphane Pateux; Vincent Gripon (CoRR, 2022)

Preserving Fine-Grain Feature Information in Classification via Entropic Regularization. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (CoRR, 2022)

Active Few-Shot Classification: a New Paradigm for Data-Scarce Learning Settings. - Aymane Abdali; Vincent Gripon; Lucas Drumetz; Bartosz Boguslawski (CoRR, 2022)

A Statistical Model for Predicting Generalization in Few-Shot Classification. - Yassir Bendou; Vincent Gripon; Bastien Pasdeloup; Lukas Mauch; Stefan Uhlich; Fabien Cardinaux; Ghouthi Boukli Hacene; Javier Alonso García (CoRR, 2022)

Easy - Ensemble Augmented-Shot-Y-Shaped Learning: State-of-the-Art Few-Shot Classification with Simple Components. - Yassir Bendou; Yuqing Hu 001; Raphaël Lafargue; Giulia Lioi; Bastien Pasdeloup; Stéphane Pateux; Vincent Gripon (J. Imaging, 2022)

Rethinking Weight Decay for Efficient Neural Network Pruning. - Hugo Tessier; Vincent Gripon; Mathieu Léonardon; Matthieu Arzel; Thomas Hannagan; David Bertrand (J. Imaging, 2022)

Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification. - Yuqing Hu 001; Stéphane Pateux; Vincent Gripon (AISTATS, 2023)

A Statistical Model for Predicting Generalization in Few-Shot Classification. - Yassir Bendou; Vincent Gripon; Bastien Pasdeloup; Giulia Lioi; Lukas Mauch; Stefan Uhlich; Fabien Cardinaux; Ghouthi Boukli Hacene; Javier Alonso García (EUSIPCO, 2023)

Active Learning for Efficient Few-Shot Classification. - Aymane Abdali; Vincent Gripon; Lucas Drumetz; Bartosz Boguslawski (ICASSP, 2023)

Entropy Based Feature Regularization to Improve Transferability of Deep Learning Models. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (ICASSP, 2023)

Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities. - Yassine El Ouahidi; Lucas Drumetz; Giulia Lioi; Nicolas Farrugia; Bastien Pasdeloup; Vincent Gripon (ICASSP, 2023)

Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach. - Yassir Bendou; Lucas Drumetz; Vincent Gripon; Giulia Lioi; Bastien Pasdeloup (CoRR, 2023)

A Strong and Simple Deep Learning Baseline for BCI MI Decoding. - Yassine El Ouahidi; Vincent Gripon; Bastien Pasdeloup; Ghaith Bouallegue; Nicolas Farrugia; Giulia Lioi (CoRR, 2023)

ThinResNet: A New Baseline for Structured Convolutional Networks Pruning. - Hugo Tessier; Ghouthi Boukli Hacene; Vincent Gripon (CoRR, 2023)

Inferring Latent Class Statistics from Text for Robust Visual Few-Shot Learning. - Yassir Bendou; Vincent Gripon; Bastien Pasdeloup; Giulia Lioi; Lukas Mauch; Fabien Cardinaux; Ghouthi Boukli Hacene (CoRR, 2023)

On Transfer in Classification: How Well do Subsets of Classes Generalize? - Raphaël Baena; Lucas Drumetz; Vincent Gripon (EUSIPCO, 2024)

Unsupervised Adaptive Deep Learning Method for BCI Motor Imagery Decoding. - Yassine El Ouahidi; Giulia Lioi; Nicolas Farrugia; Bastien Pasdeloup; Vincent Gripon (EUSIPCO, 2024)

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. - Milos Nikolic 002; Ghouthi Boukli Hacene; Ciaran Bannon; Alberto Delmas Lascorz; Matthieu Courbariaux; Omar Mohamed Awad; Isak Edo Vivancos; Yoshua Bengio; Vincent Gripon; Andreas Moshovos (ISCAS, 2024)

Design Environment of Quantization-Aware Edge AI Hardware for Few-Shot Learning. - R. Kanda; Naoya Onizawa; Mathieu Léonardon; Vincent Gripon; Takahiro Hanyu (MWSCAS, 2024)

Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes. - Raphaël Lafargue; Yassir Bendou; Bastien Pasdeloup; Jean-Philippe Diguet; Ian D. Reid 001; Vincent Gripon; Jack Valmadre (CoRR, 2024)

LLM meets Vision-Language Models for Zero-Shot One-Class Classification. - Yassir Bendou; Giulia Lioi; Bastien Pasdeloup; Lukas Mauch; Ghouthi Boukli Hacene; Fabien Cardinaux; Vincent Gripon (CoRR, 2024)

Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning. - Raphaël Lafargue; Luke Smith; Franck Vermet; Mathias Löwe; Ian D. Reid 001; Vincent Gripon; Jack Valmadre (CoRR, 2024)

Local Mixup: Interpolation of closest input signals to prevent manifold intrusion. - Raphaël Baena; Lucas Drumetz; Vincent Gripon (Signal Process., 2024)

Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning. - Raphaël Lafargue; Luke Smith; Franck Vermet; Matthias Löwe; Ian Reid 001; Jack Valmadre; Vincent Gripon (Trans. Mach. Learn. Res., 2024)

ProKeR: A Kernel Perspective on Few-Shot Adaptation of Large Vision-Language Models. - Yassir Bendou; Amine Ouasfi; Vincent Gripon; Adnane Boukhayma (CVPR, 2025)

Bit-Width-Aware Design Environment for Few-Shot Learning on Edge AI Hardware. - R. Kanda; Hugo Le Blevec; Naoya Onizawa; Mathieu Léonardon; Vincent Gripon; Takahiro Hanyu (ISCAS, 2025)

A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models. - Reda Bensaid; Vincent Gripon; François Leduc-Primeau; Lukas Mauch; Ghouthi Boukli Hacene; Fabien Cardinaux (Trans. Mach. Learn. Res., 2025)

Input Resolution Downsizing as a Compression Technique for Vision Deep Learning Systems. - Jérémy Morlier; Mathieu Léonardon; Vincent Gripon (CoRR, 2025)

Anomalous Samples for Few-Shot Anomaly Detection. - Aymane Abdali; Bartosz Boguslawski; Lucas Drumetz; Vincent Gripon (CoRR, 2025)

Object-Centric Cropping for Visual Few-Shot Classification. - Aymane Abdali; Bartosz Boguslawski; Lucas Drumetz; Vincent Gripon (CoRR, 2025)