Scholar

arXiv

Orcid

Preprints

1. Hawat, D., Gautier, G., Bardenet, R., & Lachièze-Rey, R. (2022). On estimating the structure factor of a point process, with applications to hyperuniformity. In ArXiv e-prints.
   paper arXiv code

Journal articles

1. Gautier, G., Bardenet, R., & Valko, M. (2021). Fast sampling from β-ensembles. Statistics and Computing.
   paper arXiv code
2. Gautier, G., Polito, G., Bardenet, R., & Valko, M. (2019). DPPy: DPP Sampling with Python. Journal of Machine Learning Research - Machine Learning Open Source Software (JMLR-MLOSS).
   paper arXiv code

Conference papers

1. Gautier, G., Bardenet, R., & Valko, M. (2019). On two ways to use determinantal point processes for Monte Carlo integration. Advances in Neural Information Processing Systems (NeurIPS).
   paper code poster video
2. Gautier, G., Bardenet, R., & Valko, M. (2017). Zonotope Hit-and-run for Efficient Sampling from Projection DPPs. International Conference on Machine Learning (ICML).
   paper arXiv code slides poster video

Workshop papers

1. Gautier, G., Bardenet, R., & Valko, M. (2019). On two ways to use determinantal point processes for Monte Carlo integration. Workshop on Negative Dependence in Machine Learning, International Conference on Machine Learning (ICML).
   paper code slides video
2. Gautier, G., Bardenet, R., & Valko, M. (2019). Les processus ponctuels déterminantaux en apprentissage automatique. French Colloquium on Signal and Image Processing (GRETSI).
   paper code

Thesis

1. Gautier, G. (2020). On sampling determinantal point processes (Number 2020ECLI0002) [Ph.D. thesis, École Centrale de Lille].
   paper code slides video

Popularization

1. Gautier, G., Bardenet, R., & Valko, M. (2017). Un dé pipé aux multiples facettes pour améliorer les moteurs de recherche. CNRS info - Résultats Scientifiques - Informatique.
   paper