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Nikolaos Kaplis

Researcher at Leiden University

Publications -  13
Citations -  438

Nikolaos Kaplis is an academic researcher from Leiden University. The author has contributed to research in topics: Parton & Perturbative QCD. The author has an hindex of 8, co-authored 13 publications receiving 372 citations. Previous affiliations of Nikolaos Kaplis include National and Kapodistrian University of Athens.

Papers
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Journal ArticleDOI

Constructing higher-order hydrodynamics: The third order.

TL;DR: In this article, the gradient expansion of conserved currents in terms of the fundamental fields describing the near-equilibrium fluid flow is formulated as a gradient expansion at third-order.
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From strong to weak coupling in holographic models of thermalization

TL;DR: In this paper, the authors investigated the analytic structure of thermal energy-momentum tensor correlators at large but finite coupling in quantum field theories with gravity duals, focusing on the dual to ρ = 4πkπkρεργγρεπkερεγερη ρ 4 terms in the action, and observed the appearance of new poles in the complex frequency plane at finite coupling, indicating a formation of branch cuts in the weak coupling limit.
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Bosonic excitations of the AdS 4 Reissner-Nordstrom black hole

TL;DR: In this article, the authors studied the long-lived modes of the charge density and energy density correla- tors in the stronglycoupled, finite density field theory dual to the AdS 4 Reissner-Nordstrom black hole.
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Bosonic excitations of the AdS4 Reissner-Nordstrom black hole

TL;DR: In this paper, the authors studied the long-lived modes of the charge density and energy density correlators in the stronglycoupled, finite density field theory dual to the AdS4 Reissner-Nordstrom black hole.
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A Semi-Supervised Approach to Message Stance Classification

TL;DR: This paper argues that semi-supervised learning is more effective than supervised models and uses two graph-based methods to demonstrate it, and uses the Label Propagation and Label Spreading algorithms to demonstrate their performance regarding accuracy, speed, and scalability for real-time applications.