| Bayesian workflow A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, ... arXiv preprint arXiv:2011.01808, 2020 | 615* | 2020 |
| A review of automatic differentiation and its efficient implementation CC Margossian Wiley interdisciplinary reviews: data mining and knowledge discovery 9 (4 …, 2019 | 539 | 2019 |
| Stan modeling language users guide and reference manual Stan Development Team Technical report, 2016 | 407 | 2016 |
| Estimation of SARS-CoV-2 mortality during the early stages of an epidemic: A modeling study in Hubei, China, and six regions in Europe A Hauser, MJ Counotte, CC Margossian, G Konstantinoudis, N Low, ... PLoS medicine 17 (7), e1003189, 2020 | 292* | 2020 |
| Bayesian workflow for disease transmission modeling in Stan L Grinsztajn, E Semenova, CC Margossian, J Riou Statistics in medicine 40 (27), 6209-6234, 2021 | 89 | 2021 |
| Planet hunters. VII. Discovery of a new low-mass, low-density planet (PH3 C) orbiting Kepler-289 with mass measurements of two additional planets (PH3 B and D) JR Schmitt, E Agol, KM Deck, LA Rogers, JZ Gazak, DA Fischer, J Wang, ... The Astrophysical Journal 795 (2), 167, 2014 | 72 | 2014 |
| mrgsolve: simulate from ODE-based population PK/PD and systems pharmacology models KT Baron, A Hindmarsh, L Petzold, B Gillespie, C Margossian, D Pastoor R package version 0.8 6, 2017 | 71* | 2017 |
| Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond C Margossian, A Vehtari, D Simpson, R Agrawal Advances in neural information processing systems 33, 9086-9097, 2020 | 48 | 2020 |
| Nested R ˆ: Assessing the convergence of Markov chain Monte Carlo when running many short chains CC Margossian, MD Hoffman, P Sountsov, L Riou-Durand, A Vehtari, ... Bayesian Analysis 20 (4), 1587-1614, 2025 | 35 | 2025 |
| Amortized variational inference: When and why? CC Margossian, DM Blei arXiv preprint arXiv:2307.11018, 2023 | 23 | 2023 |
| Flexible and efficient Bayesian pharmacometrics modeling using Stan and Torsten, part I CC Margossian, Y Zhang, WR Gillespie CPT: Pharmacometrics & Systems Pharmacology 11 (9), 1151-1169, 2022 | 21 | 2022 |
| Variational inference with Gaussian score matching C Modi, R Gower, C Margossian, Y Yao, D Blei, L Saul Advances in Neural Information Processing Systems 36, 29935-29950, 2023 | 17 | 2023 |
| Adaptive tuning for Metropolis adjusted Langevin trajectories L Riou-Durand, P Sountsov, J Vogrinc, C Margossian, S Power International Conference on Artificial Intelligence and Statistics, 8102-8116, 2023 | 16 | 2023 |
| Differential equations based models in stan C Margossian, B Gillespie | 16 | 2017 |
| For how many iterations should we run Markov chain Monte Carlo? CC Margossian, A Gelman arXiv preprint arXiv:2311.02726, 2023 | 15 | 2023 |
| EigenVI: score-based variational inference with orthogonal function expansions D Cai, C Modi, C Margossian, R Gower, D Blei, L Saul Advances in Neural Information Processing Systems 37, 132691-132721, 2024 | 14 | 2024 |
| The shrinkage-delinkage trade-off: An analysis of factorized gaussian approximations for variational inference CC Margossian, LK Saul Uncertainty in Artificial Intelligence, 1358-1367, 2023 | 14 | 2023 |
| The discrete adjoint method: Efficient derivatives for functions of discrete sequences M Betancourt, CC Margossian, V Leos-Barajas arXiv preprint arXiv:2002.00326, 2020 | 14 | 2020 |
| Batch and match: black-box variational inference with a score-based divergence D Cai, C Modi, L Pillaud-Vivien, CC Margossian, RM Gower, DM Blei, ... arXiv preprint arXiv:2402.14758, 2024 | 13 | 2024 |
| Variational inference for uncertainty quantification: An analysis of trade-offs CC Margossian, L Pillaud-Vivien, LK Saul Journal of Machine Learning Research 26 (202), 1-41, 2025 | 11* | 2025 |
Aki VehtariAcademy Professor, Aalto UniversityVerified email at aalto.fi
