Követés
Charles C Margossian
Charles C Margossian
Research Fellow, Flatiron Institute
E-mail megerősítve itt: flatironinstitute.org - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Bayesian workflow
A Gelman, A Vehtari, D Simpson, CC Margossian, B Carpenter, Y Yao, ...
arXiv preprint arXiv:2011.01808, 2020
3292020
A review of automatic differentiation and its efficient implementation
CC Margossian
Wiley interdisciplinary reviews: data mining and knowledge discovery 9 (4 …, 2019
3132019
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
277*2020
Stan modeling language users guide and reference manual
Stan Development Team
Technical report, 2016
2732016
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
582014
Bayesian workflow for disease transmission modeling in Stan
L Grinsztajn, E Semenova, CC Margossian, J Riou
Statistics in medicine 40 (27), 6209-6234, 2021
482021
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
39*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
352020
Nested : Assessing the convergence of Markov chain Monte Carlo when running many short chains
CC Margossian, MD Hoffman, P Sountsov, L Riou-Durand, A Vehtari, ...
arXiv preprint arXiv:2110.13017, 2021
122021
Differential equations based models in stan
C Margossian, B Gillespie
122017
The discrete adjoint method: Efficient derivatives for functions of discrete sequences
M Betancourt, CC Margossian, V Leos-Barajas
arXiv preprint arXiv:2002.00326, 2020
112020
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
82022
Stan functions for Bayesian pharmacometric modeling
C Margossian, WR Gillespie
J Pharmacokinet Pharmacodyn 43, S52, 2016
82016
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
62023
Gaining Efficiency by Combining Analytical and Numerical Solutions to Solve ODE Systems: Implementation in Stan and Application in Bayesian PKPD Modeling
CC Margossian, WR Gillespie
JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS 44, S61-S61, 2017
5*2017
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
42023
Efficient automatic differentiation of implicit functions
CC Margossian, M Betancourt
arXiv preprint arXiv:2112.14217, 2021
42021
Approximate Bayesian inference for latent Gaussian models in Stan
CC Margossian, A Vehtari, D Simpson, R Agrawal
Stan Con 2020, 2020
42020
Solving ODEs in a Bayesian context: challenges and opportunities
CC Margossian, L Zhang, S Weber, A Gelman
Population Approach Group in Europe (PAGE) 29, 2021
32021
Computing steady states with stan’s nonlinear algebraic solver
CC Margossian
Stan Conference 2018 California, 2018
32018
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Cikkek 1–20