Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization. - Louis Filstroff; Alberto Lumbreras; Cédric Févotte (ICML, 2018)

An Empirical Study of Steganography and Steganalysis of Color Images in the JPEG Domain. - Théo Taburet; Louis Filstroff; Patrick Bas; Wadih Sawaya (IWDW, 2018)

Closed-form marginal likelihood in Gamma-Poisson factorization. - Louis Filstroff; Alberto Lumbreras; Cédric Févotte (CoRR, 2018)

A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments. - Rui Xia; Vincent Y. F. Tan; Louis Filstroff; Cédric Févotte (ECML/PKDD (3), 2019)

Contributions to probabilistic non-negative matrix factorization - Maximum marginal likelihood estimation and Markovian temporal models. (Contributions à la factorisation en matrices non-négatives probabiliste - Estimation par maximum de vraisemblance marginale et modèles markoviens temporels). - Louis Filstroff (2019)

A Comparative Study of Temporal Non-Negative Matrix Factorization with Gamma Markov Chains. - Louis Filstroff; Olivier Gouvert; Cédric Févotte; Olivier Cappé (CoRR, 2020)

Bayesian mean-parameterized nonnegative binary matrix factorization. - Alberto Lumbreras; Louis Filstroff; Cédric Févotte (Data Min. Knowl. Discov., 2020)

A Comparative Study of Gamma Markov Chains for Temporal Non-Negative Matrix Factorization. - Louis Filstroff; Olivier Gouvert; Cédric Févotte; Olivier Cappé (IEEE Trans. Signal Process., 2021)

Approximate Bayesian Computation with Domain Expert in the Loop. - Ayush Bharti; Louis Filstroff; Samuel Kaski (ICML, 2022)

Bayesian Optimization Augmented with Actively Elicited Expert Knowledge. - Daolang Huang; Louis Filstroff; Petrus Mikkola; Runkai Zheng; Samuel Kaski (CoRR, 2022)

Multi-Fidelity Bayesian Optimization with Unreliable Information Sources. - Petrus Mikkola; Julien Martinelli; Louis Filstroff; Samuel Kaski (AISTATS, 2023)

Cost-aware learning of relevant contextual variables within Bayesian optimization. - Julien Martinelli; Ayush Bharti; S. T. John; Armi Tiihonen; Sabina Sloman; Louis Filstroff; Samuel Kaski (CoRR, 2023)

Learning relevant contextual variables within Bayesian optimization. - Julien Martinelli; Ayush Bharti; Armi Tiihonen; S. T. John; Louis Filstroff; Sabina J. Sloman; Patrick Rinke; Samuel Kaski (UAI, 2024)

Targeted Active Learning for Bayesian Decision-Making. - Louis Filstroff; Iiris Sundin; Petrus Mikkola; Aleksei Tiulpin; Juuso Kylmäoja; Samuel Kaski (Trans. Mach. Learn. Res., 2024)