Maestría en Ciencia de Datos: Docente Nuevo

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Docente Nuevo Nuevo

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docente@itam.mx

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agarbuno.github.io

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Intereses de investigación

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  • Problemas Inversos Bayesianos
  • Asimilación de Datos
  • Ecuaciones Diferenciales Estocásticas
  • Estadística Bayesiana no Parámetrica
  • Análisis Numérico

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Publicaciones

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Garbuno-Inigo, A., Nusken, N., and Reich, S. (2020). “Affine invariant interacting Langevin dynamics for Bayesian inference”. SIAM Journal on Applied Dynamical Systems, to appear.

Cleary, E., Garbuno-Inigo, A., Lan, S., Schneider, T., and Stuart, A.M. (2020) “Calibrate, Emulate, Sample”. Journal of Computational Physics, to appear.

Garbuno-Inigo, A., Hoffmann F., Li W., and Stuart, A.M. (2019). “Interacting Langevin Diffusions: Gradient Structure And Ensemble Kalman Sampler”. SIAM Journal on Applied Dynamical Systems, to appear.

DiazDelaO, F. A., Garbuno-Inigo, A., Au, S. K., & Yoshida, I. (2017). “Bayesian updating and model class selection with Subset Simulation”. Computer Methods in Applied Mechanics and Engineering, 317, 1102–1121.

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Cursos

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Curso de Anatomia

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El programa de la Maestría en Ciencia de Datos es una iniciativa del ITAM para satisfacer la creciente demanda nacional e internacional de profesionistas con conocimientos sólidos en el modelado a partir de datos (en especial grandes datos) para ayudar a la toma de decisiones estratégicas.

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