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Items: 16

1.

Predicting ocean rogue waves from point measurements: An experimental study for unidirectional waves.

Cousins W, Onorato M, Chabchoub A, Sapsis TP.

Phys Rev E. 2019 Mar;99(3-1):032201. doi: 10.1103/PhysRevE.99.032201.

PMID:
30999506
2.

Sequential sampling strategy for extreme event statistics in nonlinear dynamical systems.

Mohamad MA, Sapsis TP.

Proc Natl Acad Sci U S A. 2018 Oct 30;115(44):11138-11143. doi: 10.1073/pnas.1813263115. Epub 2018 Oct 16.

3.

New perspectives for the prediction and statistical quantification of extreme events in high-dimensional dynamical systems.

Sapsis TP.

Philos Trans A Math Phys Eng Sci. 2018 Aug 28;376(2127). pii: 20170133. doi: 10.1098/rsta.2017.0133. Review.

4.

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

Vlachas PR, Byeon W, Wan ZY, Sapsis TP, Koumoutsakos P.

Proc Math Phys Eng Sci. 2018 May;474(2213):20170844. doi: 10.1098/rspa.2017.0844. Epub 2018 May 23.

5.

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Wan ZY, Vlachas P, Koumoutsakos P, Sapsis T.

PLoS One. 2018 May 24;13(5):e0197704. doi: 10.1371/journal.pone.0197704. eCollection 2018.

6.

A variational approach to probing extreme events in turbulent dynamical systems.

Farazmand M, Sapsis TP.

Sci Adv. 2017 Sep 22;3(9):e1701533. doi: 10.1126/sciadv.1701533. eCollection 2017 Sep.

7.

Reduced-order description of transient instabilities and computation of finite-time Lyapunov exponents.

Babaee H, Farazmand M, Haller G, Sapsis TP.

Chaos. 2017 Jun;27(6):063103. doi: 10.1063/1.4984627.

PMID:
28679218
8.

Dynamical indicators for the prediction of bursting phenomena in high-dimensional systems.

Farazmand M, Sapsis TP.

Phys Rev E. 2016 Sep;94(3-1):032212. Epub 2016 Sep 14.

PMID:
27739820
9.

A minimization principle for the description of modes associated with finite-time instabilities.

Babaee H, Sapsis TP.

Proc Math Phys Eng Sci. 2016 Feb;472(2186):20150779.

10.

Circadian Rhythms in Rho1 Activity Regulate Neuronal Plasticity and Network Hierarchy.

Petsakou A, Sapsis TP, Blau J.

Cell. 2015 Aug 13;162(4):823-35. doi: 10.1016/j.cell.2015.07.010. Epub 2015 Jul 30.

11.

Unsteady evolution of localized unidirectional deep-water wave groups.

Cousins W, Sapsis TP.

Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Jun;91(6):063204. Epub 2015 Jun 15.

PMID:
26172815
12.

Blended particle filters for large-dimensional chaotic dynamical systems.

Majda AJ, Qi D, Sapsis TP.

Proc Natl Acad Sci U S A. 2014 May 27;111(21):7511-6. doi: 10.1073/pnas.1405675111. Epub 2014 May 13.

13.

Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

Sapsis TP, Majda AJ.

Proc Natl Acad Sci U S A. 2013 Aug 20;110(34):13705-10. doi: 10.1073/pnas.1313065110. Epub 2013 Aug 5.

14.

Lagrangian coherent structures and the smallest finite-time Lyapunov exponent.

Haller G, Sapsis T.

Chaos. 2011 Jun;21(2):023115. doi: 10.1063/1.3579597.

PMID:
21721757
15.

Instabilities on prey dynamics in jellyfish feeding.

Sapsis T, Peng J, Haller G.

Bull Math Biol. 2011 Aug;73(8):1841-56. doi: 10.1007/s11538-010-9594-4. Epub 2010 Oct 26.

PMID:
20976565
16.

Clustering criterion for inertial particles in two-dimensional time-periodic and three-dimensional steady flows.

Sapsis T, Haller G.

Chaos. 2010 Mar;20(1):017515. doi: 10.1063/1.3272711.

PMID:
20370305

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