Michaël Fanuel

According to our database, Michaël Fanuel authored at least 23 papers between 2016 and 2024.

Collaborative distances:

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

2024

Ellipsoidal embeddings of graphs.

Michaël Fanuel, Antoine Aspeel, Michael T. Schaub, Jean-Charles Delvenne

CoRR, 2024

2023

On sampling determinantal and Pfaffian point processes on a quantum computer.

Rémi Bardenet, Michaël Fanuel, Alexandre Feller

CoRR, 2023

Smoothing Complex-Valued Signals on Graphs with Monte-Carlo.

Hugo Jaquard, Michaël Fanuel, Pierre-Olivier Amblard, Rémi Bardenet, Simon Barthelmé, Nicolas Tremblay

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Determinantal Point Processes Implicitly Regularize Semiparametric Regression Problems.

Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens

SIAM J. Math. Data Sci., September, 2022

Positive Semi-definite Embedding for Dimensionality Reduction and Out-of-Sample Extensions.

Michaël Fanuel, Antoine Aspeel, Jean-Charles Delvenne, Johan A. K. Suykens

SIAM J. Math. Data Sci., 2022

Disentangled Representation Learning and Generation With Manifold Optimization.

Arun Pandey, Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens

Neural Comput., 2022

Nyström landmark sampling and regularized Christoffel functions.

Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens

Mach. Learn., 2022

Sparsification of the regularized magnetic Laplacian with multi-type spanning forests.

Michaël Fanuel, Rémi Bardenet

CoRR, 2022

2021

Diversity Sampling is an Implicit Regularization for Kernel Methods.

Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens

SIAM J. Math. Data Sci., 2021

The Bures Metric for Generative Adversarial Networks.

Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Nonparametric estimation of continuous DPPs with kernel methods.

Michaël Fanuel, Rémi Bardenet

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks.

Joachim Schreurs, Hannes De Meulemeester, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

Recovering Hölder smooth functions from noisy modulo samples.

Michaël Fanuel, Hemant Tyagi

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems.

Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens

CoRR, 2020

Ensemble Kernel Methods, Implicit Regularization and Determinental Point Processes.

Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens

CoRR, 2020

The Bures Metric for Taming Mode Collapse in Generative Adversarial Networks.

Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens

CoRR, 2020

Wasserstein Exponential Kernels.

Henri De Plaen, Michaël Fanuel, Johan A. K. Suykens

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

Robust classification of graph-based data.

Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens

Data Min. Knowl. Discov., 2019

Towards Deterministic Diverse Subset Sampling.

Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018

Convex Formulation for Kernel PCA and Its Use in Semisupervised Learning.

Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens

IEEE Trans. Neural Networks Learn. Syst., 2018

2016

Magnetic Eigenmaps for Visualization of Directed Networks.

Michaël Fanuel, Ángela Fernández, Carlos M. Alaíz, Johan A. K. Suykens

CoRR, 2016

Magnetic eigenmaps for community detection in directed networks.

Michaël Fanuel, Carlos M. Alaíz, Johan A. K. Suykens

CoRR, 2016

Convex Formulation for Kernel PCA and its Use in Semi-Supervised Learning.

Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens

CoRR, 2016