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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.

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Research Output

  • 19 Article
  • 4 Conference contribution

A deep learning solution approach for high-dimensional random differential equations

Nabian, M. A. & Meidani, H., Jul 2019, In : Probabilistic Engineering Mechanics. 57, p. 14-25 12 p.

Research output: Contribution to journalArticle

  • Development of an overweight vehicle permit fee structure for Illinois

    Gungor, O. E., Petit, A. M. A., Qiu, J., Zhao, J., Meidani, H., Wang, H., Ouyang, Y., Al-Qadi, I. L. & Mann, J., Oct 2019, In : Transport Policy. 82, p. 26-35 10 p.

    Research output: Contribution to journalArticle

  • Predicting Near-Term Train Schedule Performance and Delay Using Bi-Level Random Forests

    Nabian, M. A., Alemazkoor, N. & Meidani, H., May 1 2019, In : Transportation Research Record. 2673, 5, p. 564-573 10 p.

    Research output: Contribution to journalArticle

  • 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

  • A preconditioning approach for improved estimation of sparse polynomial chaos expansions

    Alemazkoor, N. & Meidani, H., Dec 1 2018, In : Computer Methods in Applied Mechanics and Engineering. 342, p. 474-489 16 p.

    Research output: Contribution to journalArticle