Nathan Hubens

According to our database, Nathan Hubens authored at least 13 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

A Recipe for Efficient SBIR Models: Combining Relative Triplet Loss with Batch Normalization and Knowledge Distillation.

Omar Seddati, Nathan Hubens, Stéphane Dupont, Thierry Dutoit

CoRR, 2023

Induced Feature Selection by Structured Pruning.

Nathan Hubens, Victor Delvigne, Matei Mancas, Bernard Gosselin, Marius Preda, Titus B. Zaharia

CoRR, 2023

2022

Towards lighter and faster deep neural networks with parameter pruning. (Compression et accélération de réseaux de neurones profonds par élagage synaptique).

Nathan Hubens

PhD thesis, 2022

Where Is My Mind (Looking at)? A Study of the EEG-Visual Attention Relationship.

Victor Delvigne, Noé Tits, Luca La Fisca, Nathan Hubens, Antoine Maiorca, Hazem Wannous, Thierry Dutoit, Jean-Philippe Vandeborre

Informatics, 2022

FasterAI: A Lightweight Library for Creating Sparse Neural Networks.

Nathan Hubens

CoRR, 2022

Where Is My Mind (looking at)? Predicting Visual Attention from Brain Activity.

Victor Delvigne, Noé Tits, Luca La Fisca, Nathan Hubens, Antoine Maiorca, Hazem Wannous, Thierry Dutoit, Jean-Philippe Vandeborre

CoRR, 2022

One-Cycle Pruning: Pruning Convnets With Tight Training Budget.

Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus B. Zaharia

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Improve Convolutional Neural Network Pruning by Maximizing Filter Variety.

Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus B. Zaharia

Proceedings of the Image Analysis and Processing - ICIAP 2022, 2022

Towards Lightweight Neural Animation: Exploration of Neural Network Pruning in Mixture of Experts-based Animation Models.

Antoine Maiorca, Nathan Hubens, Sohaib Laraba, Thierry Dutoit

Proceedings of the 17th International Joint Conference on Computer Vision, 2022

2021

An Experimental Study of the Impact of Pre-training on the Pruning of a Convolutional Neural Network.

Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus B. Zaharia

CoRR, 2021

One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget.

Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus B. Zaharia

CoRR, 2021

2020

An Experimental Study of the Impact of Pre-Training on the Pruning of a Convolutional Neural Network.

Nathan Hubens, Matei Mancas, Marc Decombas, Marius Preda, Titus B. Zaharia, Bernard Gosselin, Thierry Dutoit

Proceedings of the APPIS 2020: 3rd International Conference on Applications of Intelligent Systems, 2020

2019

Modulated Self-attention Convolutional Network for VQA.

Jean-Benoit Delbrouck, Antoine Maiorca, Nathan Hubens, Stéphane Dupont

CoRR, 2019