Michaël Fanuel

36 papers A* 1B 1Misc 1Journal 28Unranked 5
YearRankTypeTitle / Venue / Authors
2025 J jnl
Bypassing orthogonalization in the quantum DPP sampler.
CoRR
Michaël Fanuel, Rémi Bardenet
2025 J jnl
Ellipsoidal Embeddings of Graphs.
SIAM J. Appl. Math.
Michaël Fanuel, Antoine Aspeel, Michael T. Schaub, Jean-Charles Delvenne
2024 J jnl
Ellipsoidal embeddings of graphs.
CoRR
Michaël Fanuel, Antoine Aspeel, Michael T. Schaub, Jean-Charles Delvenne
2024 J jnl
On the Number of Steps of CyclePopping in Weakly Inconsistent U(1)-Connection Graphs.
CoRR
Michaël Fanuel, Rémi Bardenet
2023 J jnl
On sampling determinantal and Pfaffian point processes on a quantum computer.
CoRR
Rémi Bardenet, Michaël Fanuel, Alexandre Feller
2023 Misc conf
Smoothing Complex-Valued Signals on Graphs with Monte-Carlo.
ICASSP
Hugo Jaquard, Michaël Fanuel, Pierre-Olivier Amblard, Rémi Bardenet, Simon Barthelmé, Nicolas Tremblay
2022 J jnl
Determinantal Point Processes Implicitly Regularize Semiparametric Regression Problems.
SIAM J. Math. Data Sci.
Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
2022 J jnl
Disentangled Representation Learning and Generation With Manifold Optimization.
Neural Comput.
Arun Pandey, Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
2022 J jnl
Nyström landmark sampling and regularized Christoffel functions.
Mach. Learn.
Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
2022 J jnl
Positive Semi-definite Embedding for Dimensionality Reduction and Out-of-Sample Extensions.
SIAM J. Math. Data Sci.
Michaël Fanuel, Antoine Aspeel, Jean-Charles Delvenne, Johan A. K. Suykens
2022 J jnl
Sparsification of the regularized magnetic Laplacian with multi-type spanning forests.
CoRR
Michaël Fanuel, Rémi Bardenet
2021 J jnl
Diversity Sampling is an Implicit Regularization for Kernel Methods.
SIAM J. Math. Data Sci.
Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
2021 — conf
Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks.
LOD
Joachim Schreurs, Hannes De Meulemeester, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens
2021 J jnl
Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks.
CoRR
Joachim Schreurs, Hannes De Meulemeester, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens
2021 A* conf
Nonparametric estimation of continuous DPPs with kernel methods.
NeurIPS
Michaël Fanuel, Rémi Bardenet
2021 J jnl
Nonparametric estimation of continuous DPPs with kernel methods.
CoRR
Michaël Fanuel, Rémi Bardenet
2021 — conf
Recovering Hölder smooth functions from noisy modulo samples.
ACSCC
Michaël Fanuel, Hemant Tyagi
2021 — conf
The Bures Metric for Generative Adversarial Networks.
ECML/PKDD (2)
Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens
2021 J jnl
Towards Deterministic Diverse Subset Sampling.
CoRR
Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens
2020 J jnl
Determinantal Point Processes Implicitly Regularize Semi-parametric Regression Problems.
CoRR
Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
2020 J jnl
Disentangled Representation Learning and Generation with Manifold Optimization.
CoRR
Arun Pandey, Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
2020 J jnl
Diversity sampling is an implicit regularization for kernel methods.
CoRR
Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
2020 J jnl
Ensemble Kernel Methods, Implicit Regularization and Determinental Point Processes.
CoRR
Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens
2020 J jnl
The Bures Metric for Taming Mode Collapse in Generative Adversarial Networks.
CoRR
Hannes De Meulemeester, Joachim Schreurs, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens
2020 B conf
Wasserstein Exponential Kernels.
IJCNN
Henri De Plaen, Michaël Fanuel, Johan A. K. Suykens
2020 J jnl
Wasserstein Exponential Kernels.
CoRR
Henri De Plaen, Michaël Fanuel, Johan A. K. Suykens
2019 J jnl
Nyström landmark sampling and regularized Christoffel functions.
CoRR
Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
2019 J jnl
Robust classification of graph-based data.
Data Min. Knowl. Discov.
Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens
2019 — conf
Towards Deterministic Diverse Subset Sampling.
BNAIC/BENELEARN
Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens
2019 — conf
Towards Deterministic Diverse Subset Sampling.
BNAIC/BENELEARN (Selected Papers)
Joachim Schreurs, Michaël Fanuel, Johan A. K. Suykens
2018 J jnl
Convex Formulation for Kernel PCA and Its Use in Semisupervised Learning.
IEEE Trans. Neural Networks Learn. Syst.
Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens
2017 J jnl
Positive semi-definite embedding for dimensionality reduction and out-of-sample extensions.
CoRR
Michaël Fanuel, Antoine Aspeel, Jean-Charles Delvenne, Johan A. K. Suykens
2016 J jnl
Convex Formulation for Kernel PCA and its Use in Semi-Supervised Learning.
CoRR
Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens
2016 J jnl
Magnetic Eigenmaps for Visualization of Directed Networks.
CoRR
Michaël Fanuel, Ángela Fernández, Carlos M. Alaíz, Johan A. K. Suykens
2016 J jnl
Magnetic eigenmaps for community detection in directed networks.
CoRR
Michaël Fanuel, Carlos M. Alaíz, Johan A. K. Suykens
2016 J jnl
Robust Classification of Graph-Based Data.
CoRR
Carlos M. Alaíz, Michaël Fanuel, Johan A. K. Suykens