Bastien Pasdeloup

Orcid: 0000-0002-8417-7537

According to our database1, Bastien Pasdeloup authored at least 28 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Unsupervised Adaptive Deep Learning Method For BCI Motor Imagery Decoding.
CoRR, 2024

Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes.
CoRR, 2024

2023
Learning to select operators in meta-heuristics: An integration of Q-learning into the iterated greedy algorithm for the permutation flowshop scheduling problem.
Eur. J. Oper. Res., 2023

Inferring Latent Class Statistics from Text for Robust Visual Few-Shot Learning.
CoRR, 2023

A Strong and Simple Deep Learning Baseline for BCI MI Decoding.
CoRR, 2023

Disambiguation of One-Shot Visual Classification Tasks: A Simplex-Based Approach.
CoRR, 2023

Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities.
Proceedings of the IEEE International Conference on Acoustics, 2023

A Statistical Model for Predicting Generalization in Few-Shot Classification.
Proceedings of the 31st European Signal Processing Conference, 2023

2022
Easy - Ensemble Augmented-Shot-Y-Shaped Learning: State-of-the-Art Few-Shot Classification with Simple Components.
J. Imaging, 2022

A Statistical Model for Predicting Generalization in Few-Shot Classification.
CoRR, 2022

EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.
CoRR, 2022

Pruning Graph Convolutional Networks to Select Meaningful Graph Frequencies for FMRI Decoding.
Proceedings of the 30th European Signal Processing Conference, 2022

2021
Graphs as Tools to Improve Deep Learning Methods.
CoRR, 2021

A Learning-Based Iterated Local Search Algorithm for Solving the Traveling Salesman Problem.
Proceedings of the Optimization and Learning - 4th International Conference, 2021

New Insights into the Propulsion Power Prediction of Cruise Ships.
Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Improving Classification Accuracy With Graph Filtering.
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Une approche pour regrouper des sujets atteints de cancers, sur la base des similarités des répartitions cellulaires au sein de leurs biopsies.
Proceedings of the Extraction et Gestion des Connaissances, 2021

2020
An Approach for Clustering Subjects According to Similarities in Cell Distributions within Biopsies.
CoRR, 2020

2018
Characterization and Inference of Graph Diffusion Processes From Observations of Stationary Signals.
IEEE Trans. Signal Inf. Process. over Networks, 2018

2017
Extending convolutional neural networks to irregular domains through graph inference. (Extension des réseaux de neurones convolutifs à des domaines irréguliers par l'inférence de graphe).
PhD thesis, 2017

Convolutional neural networks on irregular domains through approximate translations on inferred graphs.
CoRR, 2017

Translations on graphs with neighborhood preservation.
CoRR, 2017

Evaluating graph signal processing for neuroimaging through classification and dimensionality reduction.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016
Characterization and inference of weighted graph topologies from observations of diffused signals.
CoRR, 2016

Towards a characterization of the uncertainty curve for graphs.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Neighborhood-preserving translations on graphs.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015
Toward an uncertainty principle for weighted graphs.
Proceedings of the 23rd European Signal Processing Conference, 2015

Graph reconstruction from the observation of diffused signals.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015


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