| Bayesian mean-parameterized nonnegative binary matrix factorization A Lumbreras, L Filstroff, C Févotte Data Mining and Knowledge Discovery, 1-38, 2020 | 15 | 2020 |
| 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 | 15 | 2019 |
| Approximate Bayesian Computation with Domain Expert in the Loop A Bharti, L Filstroff, S Kaski International Conference on Machine Learning, 1893-1905, 2022 | 7 | 2022 |
| Closed-form Marginal Likelihood in Gamma-Poisson Matrix Factorization L Filstroff, A Lumbreras, C Févotte International Conference on Machine Learning, 1505-1513, 2018 | 7* | 2018 |
| 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 | 6 | 2023 |
| 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 | 5 | 2019 |
| 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 | 4 | 2021 |
| 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 | 3 | 2022 |
| Bayesian Optimization Augmented with Actively Elicited Expert Knowledge D Huang, L Filstroff, P Mikkola, R Zheng, S Kaski arXiv preprint arXiv:2208.08742, 2022 | 3 | 2022 |
| Augmenting Bayesian Optimization with Preference-based Expert Feedback D Huang, L Filstroff, P Mikkola, R Zheng, M Todorovic, S Kaski ICML 2023 Workshop The Many Facets of Preference-Based Learning, 2023 | 2 | 2023 |
| 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 | 2 | 2021 |
| Contributions to probabilistic non-negative matrix factorization-Maximum marginal likelihood estimation and Markovian temporal models L Filstroff Institut National Polytechnique de Toulouse-INPT, 2019 | 1 | 2019 |
| Learning relevant contextual variables within Bayesian optimization J Martinelli, A Bharti, A Tiihonen, L Filstroff, ST John, SJ Sloman, P Rinke, ... NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in …, 2023 | | 2023 |
| 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 | | 2023 |
Samuel KaskiProfessor, Aalto University and University of Manchester在 aalto.fi 的电子邮件经过验证
