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

Large-Scale Memory of Sequences Using Binary Sparse Neural Networks on GPU. - Max Raphael Sobroza Marques; Ghouthi Boukli Hacene; Carlos Eduardo Rosar Kós Lassance; Pierre-Henri Horrein (HPCS, 2017)

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

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)

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)

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)

Processing and learning deep neural networks on chip. (Traitement et apprentissage des réseaux de neurones profonds sur puce). - Ghouthi Boukli Hacene (2019)

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

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

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)

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

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

Deeplite NeutrinoTM: A BlackBox Framework for Constrained Deep Learning Model Optimization. - Anush Sankaran; Olivier Mastropietro; Ehsan Saboori; Yasser Idris; Davis Sawyer; MohammadHossein AskariHemmat; Ghouthi Boukli Hacene (AAAI, 2021)

Deeplite Neutrino: An End-to-End Framework for Constrained Deep Learning Model Optimization. - Anush Sankaran; Olivier Mastropietro; Ehsan Saboori; Yasser Idris; Davis Sawyer; MohammadHossein AskariHemmat; Ghouthi Boukli Hacene (CoRR, 2021)

DNN Quantization with Attention. - Ghouthi Boukli Hacene; Lukas Mauch; Stefan Uhlich; Fabien Cardinaux (CoRR, 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 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)

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)

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)

Analyzing Few-Shot Neural Architecture Search in a Metric-Driven Framework. - Timotée Ly-Manson; Mathieu Léonardon; Abdeldjalil Aïssa-El-Bey; Ghouthi Boukli Hacene; Lukas Mauch (AutoML, 2024)

Skill: Similarity-Aware Knowledge Distillation for Speech Self-Supervised Learning. - Luca Zampierin; Ghouthi Boukli Hacene; Bac Nguyen; Mirco Ravanelli (ICASSP Workshops, 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)

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)

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)