Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 2 Similar Profiles
Chaos theory Engineering & Materials Science
chaos Physics & Astronomy
polynomials Physics & Astronomy
Polynomials Engineering & Materials Science
Structural dynamics Engineering & Materials Science
Markov processes Engineering & Materials Science
expansion Physics & Astronomy
Sampling Engineering & Materials Science

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Research Output 2009 2018

  • 13 Article
  • 4 Conference contribution

A near-optimal sampling strategy for sparse recovery of polynomial chaos expansions

Alemazkoor, N. & Meidani, H. Oct 15 2018 In : Journal of Computational Physics. 371, p. 137-151 15 p.

Research output: Contribution to journalArticle

Chaos theory
chaos
polynomials
recovery
sampling

Deep Learning for Accelerated Seismic Reliability Analysis of Transportation Networks

Nabian, M. A. & Meidani, H. Jun 1 2018 In : Computer-Aided Civil and Infrastructure Engineering. 33, 6, p. 443-458 16 p.

Research output: Contribution to journalArticle

reliability analysis
Reliability analysis
connectivity
learning
infrastructure
Nuclear fuels
Time series
Gases
Nuclear reactors
Principal component analysis
Railroads
Bioinformatics
Deterioration
Geometry
Defects

Calibration and ranking of coarse-grained models in molecular simulations using bayesian formalism

Meidani, H., Hooper, J. B., Bedrov, D. & Kirby, R. M. 2017 In : International Journal for Uncertainty Quantification. 7, 2, p. 99-115 17 p.

Research output: Contribution to journalArticle

Molecular Simulation
Ranking
Calibration
Prediction
Ensemble