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Highly Cited

2018

Highly Cited

2018

The graph convolutional networks (GCN) recently proposed by Kipf and Welling are an effective graph model for semi-supervised… Expand

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Highly Cited

2011

Highly Cited

2011

Structural reliability methods aim at computing the probability of failure of systems with respect to some prescribed performance… Expand

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Highly Cited

2011

Highly Cited

2011

Abstract Random graphs with given degrees are a natural next step in complexity beyond the Erdős–Rényi model, yet the degree… Expand

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Highly Cited

2010

Highly Cited

2010

1. Elements of Importance Sampling.- 2. Methods of Importance Sampling.- 3. Sums of Random Variables.- 4. Detection Theory.- 5… Expand

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Highly Cited

2009

Highly Cited

2009

. The Adaptive Multiple Importance Sampling algorithm is aimed at an optimal recycling of past simulations in an iterated… Expand

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Highly Cited

2008

Highly Cited

2008

In this paper, we propose an adaptive algorithm that iteratively updates both the weights and component parameters of a mixture… Expand

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Highly Cited

2006

Highly Cited

2006

In this paper, we propose a novel methodology for statistical SRAM design and analysis. It relies on an efficient form of… Expand

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Highly Cited

2005

Highly Cited

2005

Monte Carlo simulation is widely used to measure the credit risk in portfolios of loans, corporate bonds, and other instruments… Expand

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Highly Cited

2001

Highly Cited

2001

Simulated annealing—moving from a tractable distribution to a distribution of interest via a sequence of intermediate… Expand

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Highly Cited

1996

Highly Cited

1996

Although Markov chain Monte Carlo methods have been widely used in many disciplines, exact eigen analysis for such generated… Expand

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