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2020 – today
- 2024
[j20]Raphaël Baena
, Lucas Drumetz, Vincent Gripon:
Local Mixup: Interpolation of closest input signals to prevent manifold intrusion. Signal Process. 219: 109395 (2024)- [c73]Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Omar Mohamed Awad, Isak Edo Vivancos, Yoshua Bengio, Vincent Gripon, Andreas Moshovos:
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. ISCAS 2024: 1-5 - [i82]Reda Bensaid, Vincent Gripon, François Leduc-Primeau, Lukas Mauch, Ghouthi Boukli Hacene, Fabien Cardinaux:
A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models. CoRR abs/2401.11311 (2024) - [i81]Raphaël Lafargue, Yassir Bendou, Bastien Pasdeloup, Jean-Philippe Diguet, Ian D. Reid, Vincent Gripon, Jack Valmadre:
Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes. CoRR abs/2401.15834 (2024) - [i80]Raphaël Baena, Lucas Drumetz, Vincent Gripon:
On Transfer in Classification: How Well do Subsets of Classes Generalize? CoRR abs/2403.03569 (2024) - [i79]Yassine El Ouahidi, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon:
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding. CoRR abs/2403.15438 (2024) - [i78]Yassir Bendou, Giulia Lioi, Bastien Pasdeloup, Lukas Mauch, Ghouthi Boukli Hacene, Fabien Cardinaux, Vincent Gripon:
LLM meets Vision-Language Models for Zero-Shot One-Class Classification. CoRR abs/2404.00675 (2024) - 2023
- [c72]Yuqing Hu, Stéphane Pateux, Vincent Gripon:
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification. AISTATS 2023: 5899-5917 - [c71]Yassir Bendou, Vincent Gripon, Bastien Pasdeloup, Giulia Lioi, Lukas Mauch, Stefan Uhlich, Fabien Cardinaux, Ghouthi Boukli Hacene, Javier Alonso García:
A Statistical Model for Predicting Generalization in Few-Shot Classification. EUSIPCO 2023: 1260-1264 - [c70]Aymane Abdali, Vincent Gripon, Lucas Drumetz, Bartosz Boguslawski:
Active Learning for Efficient Few-Shot Classification. ICASSP 2023: 1-5 - [c69]Raphaël Baena, Lucas Drumetz, Vincent Gripon:
Entropy Based Feature Regularization to Improve Transferability of Deep Learning Models. ICASSP 2023: 1-5 - [c68]Yassine El Ouahidi, Lucas Drumetz, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon:
Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities. ICASSP 2023: 1-5 - [i77]Yassir Bendou, Lucas Drumetz, Vincent Gripon, Giulia Lioi, Bastien Pasdeloup:
Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach. CoRR abs/2301.06372 (2023) - [i76]Yassine El Ouahidi, Vincent Gripon, Bastien Pasdeloup, Ghaith Bouallegue, Nicolas Farrugia, Giulia Lioi:
A Strong and Simple Deep Learning Baseline for BCI MI Decoding. CoRR abs/2309.07159 (2023) - [i75]Hugo Tessier, Ghouthi Boukli Hacene, Vincent Gripon:
ThinResNet: A New Baseline for Structured Convolutional Networks Pruning. CoRR abs/2309.12854 (2023) - [i74]Yassir Bendou, Vincent Gripon, Bastien Pasdeloup, Giulia Lioi, Lukas Mauch, Fabien Cardinaux, Ghouthi Boukli Hacene:
Inferring Latent Class Statistics from Text for Robust Visual Few-Shot Learning. CoRR abs/2311.14544 (2023) - 2022
- [j19]Yuqing Hu, Stéphane Pateux, Vincent Gripon:
Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning. Algorithms 15(5): 147 (2022) - [j18]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, Thomas Hannagan, David Bertrand:
Rethinking Weight Decay for Efficient Neural Network Pruning. J. Imaging 8(3): 64 (2022) - [j17]Yassir Bendou, Yuqing Hu, Raphaël Lafargue, Giulia Lioi, Bastien Pasdeloup, Stéphane Pateux, Vincent Gripon:
Easy - Ensemble Augmented-Shot-Y-Shaped Learning: State-of-the-Art Few-Shot Classification with Simple Components. J. Imaging 8(7): 179 (2022) - [c67]Yassine El Ouahidi, Hugo Tessier, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon:
Pruning Graph Convolutional Networks to Select Meaningful Graph Frequencies for FMRI Decoding. EUSIPCO 2022: 937-941 - [c66]Raphaël Baena, Lucas Drumetz, Vincent Gripon:
A Local Mixup to Prevent Manifold Intrusion. EUSIPCO 2022: 1372-1376 - [c65]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan:
Leveraging Structured Pruning of Convolutional Neural Networks. SiPS 2022: 1-6 - [c64]Hamoud Younes, Hugo Le Blevec, Mathieu Léonardon, Vincent Gripon:
Inter-Operability of Compression Techniques for Efficient Deployment of CNNs on Microcontrollers. SYSINT 2022: 543-552 - [c63]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan:
Energy Consumption Analysis of Pruned Semantic Segmentation Networks on an Embedded GPU. SYSINT 2022: 553-563 - [i73]Raphaël Baena, Lucas Drumetz, Vincent Gripon:
Preventing Manifold Intrusion with Locality: Local Mixup. CoRR abs/2201.04368 (2022) - [i72]Yassir Bendou, Yuqing Hu, Raphaël Lafargue, Giulia Lioi, Bastien Pasdeloup, Stéphane Pateux, Vincent Gripon:
EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. CoRR abs/2201.09699 (2022) - [i71]Yassine El Ouahidi, Hugo Tessier, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon:
Pruning Graph Convolutional Networks to select meaningful graph frequencies for fMRI decoding. CoRR abs/2203.04455 (2022) - [i70]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan:
Leveraging Structured Pruning of Convolutional Neural Networks. CoRR abs/2206.06247 (2022) - [i69]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, David Bertrand, Thomas Hannagan:
Energy Consumption Analysis of pruned Semantic Segmentation Networks on an Embedded GPU. CoRR abs/2206.06255 (2022) - [i68]Raphaël Baena, Lucas Drumetz, Vincent Gripon:
Preserving Fine-Grain Feature Information in Classification via Entropic Regularization. CoRR abs/2208.03684 (2022) - [i67]Yuqing Hu, Stéphane Pateux, Vincent Gripon:
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification. CoRR abs/2209.08527 (2022) - [i66]Aymane Abdali, Vincent Gripon, Lucas Drumetz, Bartosz Boguslawski:
Active Few-Shot Classification: a New Paradigm for Data-Scarce Learning Settings. CoRR abs/2209.11481 (2022) - [i65]Yassine El Ouahidi, Lucas Drumetz, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon:
Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities. CoRR abs/2211.02624 (2022) - [i64]Yassir Bendou, Vincent Gripon, Bastien Pasdeloup, Lukas Mauch, Stefan Uhlich, Fabien Cardinaux, Ghouthi Boukli Hacene, Javier Alonso García:
A Statistical Model for Predicting Generalization in Few-Shot Classification. CoRR abs/2212.06461 (2022) - 2021
- [j16]Carlos Lassance, Vincent Gripon, Antonio Ortega:
Representing Deep Neural Networks Latent Space Geometries with Graphs. Algorithms 14(2): 39 (2021) - [j15]Myriam Bontonou, Louis Béthune, Vincent Gripon:
Predicting the Generalization Ability of a Few-Shot Classifier. Inf. 12(1): 29 (2021) - [j14]Carlos Lassance, Yasir Latif, Ravi Garg, Vincent Gripon, Ian Reid:
Improved Visual Localization via Graph Filtering. J. Imaging 7(2): 20 (2021) - [j13]Pierre-Emmanuel Novac, Ghouthi Boukli Hacene, Alain Pegatoquet, Benoît Miramond, Vincent Gripon:
Quantization and Deployment of Deep Neural Networks on Microcontrollers. Sensors 21(9): 2984 (2021) - [c62]Myriam Bontonou, Nicolas Farrugia, Vincent Gripon:
Similarity between Base and Novel Classes: a Predictor of the Performance in Few-Shot Classification of Brain Activation Maps? ACSCC 2021: 1288-1291 - [c61]Myriam Bontonou, Giulia Lioi, Nicolas Farrugia, Vincent Gripon:
Few-Shot Decoding of Brain Activation Maps. EUSIPCO 2021: 1326-1330 - [c60]Raphaël Baena, Lucas Drumetz, Vincent Gripon:
Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks. EUSIPCO 2021: 2169-2173 - [c59]Yuqing Hu, Vincent Gripon, Stéphane Pateux:
Leveraging the Feature Distribution in Transfer-Based Few-Shot Learning. ICANN (2) 2021: 487-499 - [c58]Théo Giraudon, Vincent Gripon, Matthias Löwe, Franck Vermet:
Towards an Intrinsic Definition of Robustness for a Classifier. ICASSP 2021: 4015-4019 - [c57]Mounia Hamidouche, Carlos Lassance, Yuqing Hu, Lucas Drumetz, Bastien Pasdeloup, Vincent Gripon:
Improving Classification Accuracy With Graph Filtering. ICIP 2021: 334-338 - [c56]Mathieu Léonardon, Vincent Gripon:
Using Deep Neural Networks to Predict and Improve the Performance of Polar Codes. ISTC 2021: 1-5 - [i63]Mounia Hamidouche, Carlos Lassance, Yuqing Hu, Lucas Drumetz, Bastien Pasdeloup, Vincent Gripon:
Improving Classification Accuracy with Graph Filtering. CoRR abs/2101.04789 (2021) - [i62]Raphaël Baena, Lucas Drumetz, Vincent Gripon:
Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks. CoRR abs/2102.09493 (2021) - [i61]Mathieu Léonardon, Vincent Gripon:
Using Deep Neural Networks to Predict and Improve the Performance of Polar Codes. CoRR abs/2105.04922 (2021) - [i60]Pierre-Emmanuel Novac, Ghouthi Boukli Hacene, Alain Pegatoquet, Benoît Miramond, Vincent Gripon:
Quantization and Deployment of Deep Neural Networks on Microcontrollers. CoRR abs/2105.13331 (2021) - [i59]Myriam Bontonou, Nicolas Farrugia, Vincent Gripon:
Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification. CoRR abs/2108.10427 (2021) - [i58]Carlos Lassance, Myriam Bontonou, Mounia Hamidouche, Bastien Pasdeloup, Lucas Drumetz, Vincent Gripon:
Graphs as Tools to Improve Deep Learning Methods. CoRR abs/2110.03999 (2021) - [i57]Yuqing Hu, Vincent Gripon, Stéphane Pateux:
Squeezing Backbone Feature Distributions to the Max for Efficient Few-Shot Learning. CoRR abs/2110.09446 (2021) - 2020
- [b2]Vincent Gripon:
Efficient Representations for Graph and Neural Network Signals. (Représentations efficaces pour les signaux sur graphes et réseaux de neurones). École normale supérieure de Lyon, France, 2020 - [c55]Carlos Lassance, Myriam Bontonou, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Deep Geometric Knowledge Distillation with Graphs. ICASSP 2020: 8484-8488 - [c54]Lyes Khacef, Vincent Gripon, Benoît Miramond:
GPU-Based Self-Organizing Maps for Post-labeled Few-Shot Unsupervised Learning. ICONIP (2) 2020: 404-416 - [c53]Ghouthi Boukli Hacene, Carlos Lassance, Vincent Gripon, Matthieu Courbariaux, Yoshua Bengio:
Attention Based Pruning for Shift Networks. ICPR 2020: 4054-4061 - [c52]Yuqing Hu, Vincent Gripon, Stéphane Pateux:
Graph-based Interpolation of Feature Vectors for Accurate Few-Shot Classification. ICPR 2020: 8164-8171 - [c51]Carlos Lassance, Vincent Gripon, Gonzalo Mateos:
Graph Topology Inference Benchmarks for Machine Learning. MLSP 2020: 1-6 - [c50]Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio:
Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks. NEWCAS 2020: 206-209 - [i56]Yuqing Hu, Vincent Gripon, Stéphane Pateux:
Exploiting Unsupervised Inputs for Accurate Few-Shot Classification. CoRR abs/2001.09849 (2020) - [i55]Milos Nikolic, Ghouthi Boukli Hacene, Ciaran Bannon, Alberto Delmas Lascorz, Matthieu Courbariaux, Yoshua Bengio, Vincent Gripon, Andreas Moshovos:
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization. CoRR abs/2002.03090 (2020) - [i54]Yuqing Hu, Vincent Gripon, Stéphane Pateux:
Leveraging the Feature Distribution in Transfer-based Few-Shot Learning. CoRR abs/2006.03806 (2020) - [i53]Théo Giraudon, Vincent Gripon, Matthias Löwe, Franck Vermet:
Towards an Intrinsic Definition of Robustness for a Classifier. CoRR abs/2006.05095 (2020) - [i52]Myriam Bontonou, Louis Béthune, Vincent Gripon:
Predicting the Accuracy of a Few-Shot Classifier. CoRR abs/2007.04238 (2020) - [i51]Carlos Lassance, Vincent Gripon, Gonzalo Mateos:
Graph topology inference benchmarks for machine learning. CoRR abs/2007.08216 (2020) - [i50]Guillaume Coiffier, Ghouthi Boukli Hacene, Vincent Gripon:
ThriftyNets : Convolutional Neural Networks with Tiny Parameter Budget. CoRR abs/2007.10106 (2020) - [i49]Lyes Khacef, Vincent Gripon, Benoît Miramond:
GPU-based Self-Organizing Maps for Post-Labeled Few-Shot Unsupervised Learning. CoRR abs/2009.03665 (2020) - [i48]Vincent Gripon, Matthias Löwe, Franck Vermet:
Some Remarks on Replicated Simulated Annealing. CoRR abs/2009.14702 (2020) - [i47]Myriam Bontonou, Nicolas Farrugia, Vincent Gripon:
Few-shot Learning for Decoding Brain Signals. CoRR abs/2010.12500 (2020) - [i46]Carlos Lassance, Vincent Gripon, Antonio Ortega:
Representing Deep Neural Networks Latent Space Geometries with Graphs. CoRR abs/2011.07343 (2020) - [i45]Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel, Thomas Hannagan, David Bertrand:
Continuous Pruning of Deep Convolutional Networks Using Selective Weight Decay. CoRR abs/2011.10520 (2020) - [i44]Carlos Lassance, Louis Béthune, Myriam Bontonou, Mounia Hamidouche, Vincent Gripon:
Ranking Deep Learning Generalization using Label Variation in Latent Geometry Graphs. CoRR abs/2011.12737 (2020) - [i43]Vincent Gripon, Carlos Lassance, Ghouthi Boukli Hacene:
DecisiveNets: Training Deep Associative Memories to Solve Complex Machine Learning Problems. CoRR abs/2012.01509 (2020)
2010 – 2019
- 2019
- [j12]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative Memories. J. Signal Process. Syst. 91(9): 1063-1073 (2019) - [c49]Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Jian Tang, Antonio Ortega:
Structural Robustness for Deep Learning Architectures. DSW 2019: 125-129 - [c48]Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Introducing Graph Smoothness Loss for Training Deep Learning Architectures. DSW 2019: 160-164 - [c47]Quentin Jodelet, Vincent Gripon, Masafumi Hagiwara:
Transfer Learning with Sparse Associative Memories. ICANN (1) 2019: 497-512 - [c46]Ghouthi Boukli Hacene, François Leduc-Primeau, Amal Ben Soussia, Vincent Gripon, François Gagnon:
Training Modern Deep Neural Networks for Memory-Fault Robustness. ISCAS 2019: 1-5 - [c45]Ghouthi B. Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Efficient Hardware Implementation of Incremental Learning and Inference on Chip. NEWCAS 2019: 1-4 - [i42]Quentin Jodelet, Vincent Gripon, Masafumi Hagiwara:
Transfer Learning with Sparse Associative Memories. CoRR abs/1904.02420 (2019) - [i41]Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Introducing Graph Smoothness Loss for Training Deep Learning Architectures. CoRR abs/1905.00301 (2019) - [i40]Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Jean-Charles Vialatte, Vincent Gripon:
A Unified Deep Learning Formalism For Processing Graph Signals. CoRR abs/1905.00496 (2019) - [i39]Ghouthi Boukli Hacene, Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Matthieu Courbariaux, Yoshua Bengio:
Attention Based Pruning for Shift Networks. CoRR abs/1905.12300 (2019) - [i38]Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Nicolas Farrugia:
Comparing linear structure-based and data-driven latent spatial representations for sequence prediction. CoRR abs/1908.06868 (2019) - [i37]Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Jian Tang, Antonio Ortega:
Structural Robustness for Deep Learning Architectures. CoRR abs/1909.05095 (2019) - [i36]Carlos Eduardo Rosar Kós Lassance, Yasir Latif, Ravi Garg, Vincent Gripon, Ian D. Reid:
Improved Visual Localization via Graph Smoothing. CoRR abs/1911.02961 (2019) - [i35]Carlos Eduardo Rosar Kós Lassance, Myriam Bontonou, Ghouthi Boukli Hacene, Vincent Gripon, Jian Tang, Antonio Ortega:
Deep geometric knowledge distillation with graphs. CoRR abs/1911.03080 (2019) - [i34]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Efficient Hardware Implementation of Incremental Learning and Inference on Chip. CoRR abs/1911.07847 (2019) - [i33]Ghouthi Boukli Hacene, François Leduc-Primeau, Amal Ben Soussia, Vincent Gripon, François Gagnon:
Training Modern Deep Neural Networks for Memory-Fault Robustness. CoRR abs/1911.10287 (2019) - 2018
- [j11]Ahmad Mheich, Mahmoud Hassan, Mohamad Khalil, Vincent Gripon, Olivier Dufor, Fabrice Wendling:
SimiNet: A Novel Method for Quantifying Brain Network Similarity. IEEE Trans. Pattern Anal. Mach. Intell. 40(9): 2238-2249 (2018) - [j10]Ahmet Iscen, Teddy Furon, Vincent Gripon, Michael G. Rabbat, Hervé Jégou:
Memory Vectors for Similarity Search in High-Dimensional Spaces. IEEE Trans. Big Data 4(1): 65-77 (2018) - [j9]Bastien Pasdeloup, Vincent Gripon, Grégoire Mercier, Dominique Pastor, Michael G. Rabbat:
Characterization and Inference of Graph Diffusion Processes From Observations of Stationary Signals. IEEE Trans. Signal Inf. Process. over Networks 4(3): 481-496 (2018) - [c44]Carlos Eduardo Rosar Kós Lassance, Jean-Charles Vialatte, Vincent Gripon:
Matching Convolutional Neural Networks without Priors about Data. DSW 2018: 234-238 - [c43]Nicolas Grelier, Carlos Eduardo Rosar Kós Lassance, Elsa Dupraz, Vincent Gripon:
Graph-Projected Signal Processing. GlobalSIP 2018: 763-767 - [c42]Vincent Gripon, Ghouthi B. Hacene, Matthias Löwe, Franck Vermet:
Improving Accuracy of Nonparametric Transfer Learning Via Vector Segmentation. ICASSP 2018: 2966-2970 - [c41]Vincent Gripon, Antonio Ortega, Benjamin Girault:
An Inside Look at Deep Neural Networks Using Graph Signal Processing. ITA 2018: 1-9 - [i32]Carlos Eduardo Rosar Kós Lassance, Jean-Charles Vialatte, Vincent Gripon:
Matching Convolutional Neural Networks without Priors about Data. CoRR abs/1802.09802 (2018) - [i31]Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Antonio Ortega:
Laplacian Power Networks: Bounding Indicator Function Smoothness for Adversarial Defense. CoRR abs/1805.10133 (2018) - [i30]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Transfer Incremental Learning using Data Augmentation. CoRR abs/1810.02020 (2018) - [i29]Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio:
Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks. CoRR abs/1812.11337 (2018) - 2017
- [c40]Vincent Gripon:
Tropical graph signal processing. ACSSC 2017: 50-54 - [c39]Mathilde Ménoret, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon:
Evaluating graph signal processing for neuroimaging through classification and dimensionality reduction. GlobalSIP 2017: 618-622 - [c38]Jean-Charles Vialatte, Vincent Gripon, Gilles Coppin:
Learning local receptive fields and their weight sharing scheme on graphs. GlobalSIP 2017: 623-627 - [c37]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Incremental learning on chip. GlobalSIP 2017: 789-792 - [c36]Mostafa Rizk, Jean-Philippe Diguet, Naoya Onizawa, Amer Baghdadi, Martha Johanna Sepúlveda, Y. Akgul, Vincent Gripon, Takahiro Hanyu:
NoC-MRAM architecture for memory-based computing: Database-search case study. NEWCAS 2017: 309-312 - [c35]Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel:
Budget restricted incremental learning with pre-trained convolutional neural networks and binary associative memories. SiPS 2017: 1-6 - [i28]Mathilde Ménoret, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon:
Evaluating Graph Signal Processing for Neuroimaging Through Classification and Dimensionality Reduction. CoRR abs/1703.01842 (2017) - [i27]Jean-Charles Vialatte, Vincent Gripon, Gilles Coppin:
Learning Local Receptive Fields and their Weight Sharing Scheme on Graphs. CoRR abs/1706.02684 (2017) - [i26]Bastien Pasdeloup, Vincent Gripon, Nicolas Grelier, Jean-Charles Vialatte, Dominique Pastor:
Translations on graphs with neighborhood preservation. CoRR abs/1709.03859 (2017) - [i25]Eliott Coyac, Vincent Gripon, Charlotte Langlais, Claude Berrou:
Robust Associative Memories Naturally Occuring From Recurrent Hebbian Networks Under Noise. CoRR abs/1709.08367 (2017) - [i24]Vincent Gripon, Ghouthi B. Hacene, Matthias Löwe, Franck Vermet:
Improving Accuracy of Nonparametric Transfer Learning via Vector Segmentation. CoRR abs/1710.08637 (2017) - [i23]Bastien Pasdeloup, Vincent Gripon, Jean-Charles Vialatte, Dominique Pastor:
Convolutional neural networks on irregular domains through approximate translations on inferred graphs. CoRR abs/1710.10035 (2017) - 2016
- [j8]Ala Aboudib, Vincent Gripon, Gilles Coppin:
A Biologically Inspired Framework for Visual Information Processing and an Application on Modeling Bottom-Up Visual Attention. Cogn. Comput. 8(6): 1007-1026 (2016) - [j7]Bartosz Boguslawski, Vincent Gripon, Fabrice Seguin, Frédéric Heitzmann:
Twin Neurons for Efficient Real-World Data Distribution in Networks of Neural Cliques: Applications in Power Management in Electronic Circuits. IEEE Trans. Neural Networks Learn. Syst. 27(2): 375-387 (2016) - [j6]Xiaoran Jiang, Vincent Gripon, Claude Berrou, Michael G. Rabbat:
Storing Sequences in Binary Tournament-Based Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 27(5): 913-925 (2016) - [j5]François Leduc-Primeau, Vincent Gripon, Michael G. Rabbat, Warren J. Gross:
Fault-Tolerant Associative Memories Based on c-Partite Graphs. IEEE Trans. Signal Process. 64(4): 829-841 (2016) - [c34]Robin Danilo, Hugues Nono Wouafo, Cyrille Chavet, Vincent Gripon, Laura Conde-Canencia, Philippe Coussy:
Associative Memory based on clustered Neural Networks: Improved model and architecture for Oriented Edge Detection. DASIP 2016: 51-58 - [c33]Nicolas Grelier, Bastien Pasdeloup, Jean-Charles Vialatte, Vincent Gripon:
Neighborhood-preserving translations on graphs. GlobalSIP 2016: 410-414 - [c32]Guillaume Soulié, Vincent Gripon, Maëlys Robert:
Compression of Deep Neural Networks on the Fly. ICANN (2) 2016: 153-160 - [c31]Ala Aboudib, Vincent Gripon, Gilles Coppin:
A Neural Network Model for Solving the Feature Correspondence Problem. ICANN (2) 2016: 439-446 - [c30]Bastien Pasdeloup, Vincent Gripon, Grégoire Mercier, Dominique Pastor:
Towards a characterization of the uncertainty curve for graphs. ICASSP 2016: 4558-4562 - [c29]