| A new Bayesian approach to robustness against outliers in linear regression P Gagnon, A Desgagné, M Bédard Bayesian Analysis 15 (2), 389-414, 2020 | 33 | 2020 |
| Bayesian robustness to outliers in linear regression and ratio estimation A Desgagné, P Gagnon Brazilian Journal of Probability and Statistics 33 (2), 205-221, 2019 | 22 | 2019 |
| Optimal scaling of random walk Metropolis algorithms using Bayesian large-sample asymptotics SM Schmon, P Gagnon Statistics and Computing 32 (2), 28, 2022 | 18 | 2022 |
| Nonreversible jump algorithms for Bayesian nested model selection P Gagnon, A Doucet Journal of Computational and Graphical Statistics 30 (2), 312-323, 2020 | 15 | 2020 |
| Informed reversible jump algorithms P Gagnon Electronic Journal of Statistics 15 (2), 3951-3995, 2021 | 13 | 2021 |
| An automatic robust Bayesian approach to principal component regression P Gagnon, M Bédard, A Desgagné Journal of Applied Statistics 48 (1), 84-104, 2021 | 12 | 2021 |
| An asymptotic Peskun ordering and its application to lifted samplers P Gagnon, F Maire Bernoulli 30 (3), 2301-2325, 2024 | 8 | 2024 |
| Theoretical properties of Bayesian Student-t linear regression P Gagnon, Y Hayashi Statistics & Probability Letters 193, 109693, 2023 | 8 | 2023 |
| Improving multiple-try Metropolis with local balancing P Gagnon, F Maire, G Zanella Journal of Machine Learning Research 24 (248), 1-59, 2023 | 7 | 2023 |
| Weak convergence and optimal tuning of the reversible jump algorithm P Gagnon, M Bédard, A Desgagné Mathematics and Computers in Simulation 161, 32-51, 2019 | 5 | 2019 |
| Robustness against conflicting prior information in regression P Gagnon Bayesian Analysis 18 (3), 841-864, 2023 | 3 | 2023 |
| Robust heavy-tailed versions of generalized linear models with applications in actuarial science P Gagnon, Y Wang Computational Statistics & Data Analysis 194, 107920, 2024 | 2 | 2024 |
| Theoretical guarantees for lifted samplers P Gagnon, F Maire arXiv preprint arXiv:2405.15952, 2024 | 2 | 2024 |
| Simple proof of robustness for Bayesian heavy-tailed linear regression models P Gagnon arXiv preprint arXiv:2501.06349, 2025 | | 2025 |
| On a fundamental difference between Bayesian and frequentist approaches to robustness P Gagnon, A Desgagné arXiv preprint arXiv:2408.10478, 2024 | | 2024 |
Sebastian M SchmonSenior Staff AI/MLstats.ox.ac.uk üzerinde doğrulanmış e-posta adresine sahip
Arnaud DoucetGoogle DeepMindgoogle.com üzerinde doğrulanmış e-posta adresine sahip
Giacomo ZanellaBocconi Universityunibocconi.it üzerinde doğrulanmış e-posta adresine sahip
Florian MaireUniversité de Montréal