Stochastic Variational Method for Viscous Hydrodynamics
In this short review, we focus on some of the subjects, related to J. Cleymans’ pioneering contribution of statistical approaches to the particle production process in heavy-ion collisions.
Takeshi Kodama, Tomoi Koide
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GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders [PDF]
Deep learning on graphs has become a popular research topic with many applications. However, past work has concentrated on learning graph embedding tasks, which is in contrast with advances in generative models for images and text.
M. Simonovsky, N. Komodakis
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Variational method for locating invariant tori [PDF]
We formulate a variational fictitious-time flow which drives an initial guess torus to a torus invariant under given dynamics. The method is general and applies in principle to continuous time flows and discrete time maps in arbitrary dimension, and to ...
Chandre, Cristel +2 more
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Variational Adversarial Active Learning [PDF]
Active learning aims to develop label-efficient algorithms by sampling the most representative queries to be labeled by an oracle. We describe a pool-based semi-supervised active learning algorithm that implicitly learns this sampling mechanism in an ...
Samarth Sinha +2 more
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Solution to the 3-Loop $\Phi$-Derivable Approximation for Massless Scalar Thermodynamics [PDF]
We develop a systematic method for solving the 3-loop $\Phi$-derivable approximation to the thermodynamics of the massless $\phi^4$ field theory. The method involves expanding sum-integrals in powers of $g^2$ and m/T, where g is the coupling constant, m ...
A. Peshier +31 more
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Further validation to the variational method to obtain flow relations for generalized Newtonian fluids [PDF]
We continue our investigation to the use of the variational method to derive flow relations for generalized Newtonian fluids in confined geometries.
Sochi, Taha
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Performance comparison between maximum likelihood estimation and variational method for estimating simple linear regression parameter [PDF]
Variational estimation method is a deterministic approximation technique which involves Bayesian framework while giving a point estimate instead of the usual Bayesian interval estimation. The linear regression model, which has always been a popular model,
Widyaningsih Yekti +2 more
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Tseng's forward-backward-forward algorithm is a valuable alternative for Korpelevich's extragradient method when solving variational inequalities over a convex and closed set governed by monotone and Lipschitz continuous operators, as it requires in ...
Bot, Radu Ioan +2 more
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Low-temperature excitations within the Bethe approximation [PDF]
We propose the variational quantum cavity method to construct a minimal energy subspace of wave vectors that are used to obtain some upper bounds for the energy cost of the low-temperature excitations. Given a trial wave function we use the cavity method
Biazzo, I., Ramezanpour, A.
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An Application of He's Variational Iteration Method for Solving Duffing - Van Der Pol Equation [PDF]
In this paper, we apply He's variational iteration method (VIM) and the Adomian decomposition method (ADM) to approximate the solution of Duffing-Van Der Pol equation (DVP).
Ann Al-Sawoor, Merna Samarchi
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