Louis Filstroff
Louis Filstroff
Aalto University, Department of Computer Science
Verified email at - Homepage
Cited by
Cited by
An empirical study of steganography and steganalysis of color images in the JPEG domain
T Taburet, L Filstroff, P Bas, W Sawaya
Digital Forensics and Watermarking: 17th International Workshop, IWDW 2018 …, 2019
Bayesian mean-parameterized nonnegative binary matrix factorization
A Lumbreras, L Filstroff, C Févotte
Data Mining and Knowledge Discovery, 1-38, 2020
Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization
L Filstroff, A Lumbreras, C Févotte
International Conference on Machine Learning, 1505-1513, 2018
Approximate Bayesian Computation with Domain Expert in the Loop
A Bharti, L Filstroff, S Kaski
International Conference on Machine Learning, 1893-1905, 2022
A ranking model motivated by nonnegative matrix factorization with applications to tennis tournaments
R Xia, VYF Tan, L Filstroff, C Févotte
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019
Targeted Active Learning for Bayesian Decision-Making
L Filstroff, I Sundin, P Mikkola, A Tiulpin, J Kylmäoja, S Kaski
arXiv preprint arXiv:2106.04193, 2021
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources
P Mikkola, J Martinelli, L Filstroff, S Kaski
International Conference on Artificial Intelligence and Statistics, 7425-7454, 2023
Bayesian Optimization Augmented with Actively Elicited Expert Knowledge
D Huang, L Filstroff, P Mikkola, R Zheng, S Kaski
arXiv preprint arXiv:2208.08742, 2022
A Comparative Study of Gamma Markov Chains for Temporal Non-Negative Matrix Factorization
L Filstroff, O Gouvert, C Févotte, O Cappé
IEEE Transactions on Signal Processing 69, 1614-1626, 2021
Contributions to probabilistic non-negative matrix factorization-Maximum marginal likelihood estimation and Markovian temporal models
L Filstroff
Cost-aware learning of relevant contextual variables within Bayesian optimization
J Martinelli, A Bharti, ST John, A Tiihonen, S Sloman, L Filstroff, S Kaski
arXiv preprint arXiv:2305.14120, 2023
More trustworthy Bayesian optimization of materials properties by adding human into the loop
A Tiihonen, L Filstroff, P Mikkola, E Lehto, S Kaski, M Todorović, P Rinke
AI for Accelerated Materials Design NeurIPS 2022 Workshop, 2022
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