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Carlos Améndola
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2020 – today
- 2024
- [j9]Carlos Améndola, Kathlén Kohn, Philipp Reichenbach, Anna Seigal
:
Corrigendum: Invariant Theory and Scaling Algorithms for Maximum Likelihood Estimation. SIAM J. Appl. Algebra Geom. 8(2): 460-463 (2024) - [j8]Carlos Améndola, Lukas Gustafsson, Kathlén Kohn, Orlando Marigliano
Differential Equations for Gaussian Statistical Models with Rational Maximum Likelihood Estimator. SIAM J. Appl. Algebra Geom. 8(3): 465-492 (2024) - [j7]Carlos Améndola, Kathlén Kohn, Philipp Reichenbach, Anna Seigal:
A Bridge between Invariant Theory and Maximum Likelihood Estimation. SIAM Rev. 66(4): 721-747 (2024) - 2023
- [j6]Philipp Dettling, Roser Homs, Carlos Améndola, Mathias Drton, Niels Richard Hansen
Identifiability in Continuous Lyapunov Models. SIAM J. Matrix Anal. Appl. 44(4): 1799-1821 (2023) - [c4]Carlos Améndola
Convex Hulls of Curves: Volumes and Signatures. GSI (1) 2023: 455-464 - 2022
- [j5]Carlos Améndola
Autocovariance varieties of moving average random fields. J. Symb. Comput. 109: 202-219 (2022) - 2021
- [j4]Daniele Agostini
Moment Identifiability of Homoscedastic Gaussian Mixtures. Found. Comput. Math. 21(3): 695-724 (2021) - [j3]Carlos Améndola, Kathlén Kohn
Invariant Theory and Scaling Algorithms for Maximum Likelihood Estimation. SIAM J. Appl. Algebra Geom. 5(2): 304-337 (2021) - [c3]Carlos Améndola, Benjamin Hollering
Markov equivalence of max-linear Bayesian networks. UAI 2021: 1746-1755 - 2020
- [c2]Carlos Améndola, Philipp Dettling, Mathias Drton, Federica Onori, Jun Wu:
Structure Learning for Cyclic Linear Causal Models. UAI 2020: 999-1008
2010 – 2019
- 2019
- [j2]Carlos Améndola
The maximum likelihood degree of toric varieties. J. Symb. Comput. 92: 222-242 (2019) - [j1]Daniele Agostini
Discrete Gaussian Distributions via Theta Functions. SIAM J. Appl. Algebra Geom. 3(1): 1-30 (2019) - 2015
- [c1]Carlos Améndola
Maximum Likelihood Estimates for Gaussian Mixtures Are Transcendental. MACIS 2015: 579-590
Coauthor Index
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