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Some simple effective approximations to the 2Poisson model for probabilistic weighted retrieval
 In Proceedings of SIGIR’94
, 1994
"... The 2–Poisson model for term frequencies is used to suggest ways of incorporating certain variables in probabilistic models for information retrieval. The variables concerned are withindocument term frequency, document length, and withinquery term frequency. Simple weighting functions are develope ..."
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Cited by 461 (14 self)
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The 2–Poisson model for term frequencies is used to suggest ways of incorporating certain variables in probabilistic models for information retrieval. The variables concerned are withindocument term frequency, document length, and withinquery term frequency. Simple weighting functions
The Bivariate 2Poisson model for IR
"... Harter’s 2Poisson model of Information Retrieval is a univariate model of the raw term frequencies, that does not condition the probabilities on document length [2]. A bivariate stochastic model is thus introduced to extend Harter’s 2Poisson model, by conditioning the term frequencies of the docum ..."
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Harter’s 2Poisson model of Information Retrieval is a univariate model of the raw term frequencies, that does not condition the probabilities on document length [2]. A bivariate stochastic model is thus introduced to extend Harter’s 2Poisson model, by conditioning the term frequencies
A 2poisson model for probabilistic coreference of named entities for improved text retrieval
 In Proceedings of SIGIR. Rodney
, 2009
"... Text retrieval queries frequently contain named entities. The standard approach of term frequency weighting does not work well when estimating the term frequency of a named entity, since anaphoric expressions (like he, she, the movie, etc) are frequently used to refer to named entities in a document ..."
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Cited by 4 (0 self)
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document, and the use of anaphoric expressions causes the term frequency of named entities to be underestimated. In this paper, we propose a novel 2Poisson model to estimate the frequency of anaphoric expressions of a named entity, without explicitly resolving the anaphoric expressions. Our key assumption
Posterior Predictive Assessment of Model Fitness Via Realized Discrepancies
 Statistica Sinica
, 1996
"... Abstract: This paper considers Bayesian counterparts of the classical tests for goodness of fit and their use in judging the fit of a single Bayesian model to the observed data. We focus on posterior predictive assessment, in a framework that also includes conditioning on auxiliary statistics. The B ..."
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Cited by 347 (39 self)
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with three applied examples. The first example, which serves mainly to motivate the work, illustrates the difficulty of classical tests in assessing the fitness of a Poisson model to a positron emission tomography image that is constrained to be nonnegative. The second and third examples illustrate
AmongSite Rate Variation and Its Impact on Phylogenetic Analyses
, 1996
"... ld follow a Poisson distribution. Fitch and Margoliasht counted the minimum number of nucleotide changes at each site in cytochrome c, and found that the Poisson distribution did not fit the data unless a certain num ber of 'invariant' and 'hypermutable' sites were excluded. The ..."
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Cited by 227 (11 self)
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ld follow a Poisson distribution. Fitch and Margoliasht counted the minimum number of nucleotide changes at each site in cytochrome c, and found that the Poisson distribution did not fit the data unless a certain num ber of 'invariant' and 'hypermutable' sites were excluded
Making Greed Work in Networks: A GameTheoretic Analysis of Switch Service Disciplines
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 1994
"... This paper discusses congestion control from a gametheoretic perspective. There are two basic premises: (1) users are assumed to be independent and selfish, and (2) central administrative control is exercised only at the network switches. The operating points resulting from selfish user behavior ..."
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Cited by 219 (11 self)
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behavior depend crucially on the service disciplines implemented in network switches. This effect is investigated in a simple model consisting of a single exponential server shared by many Poisson sources. We discuss the extent to which one can guarantee, through the choice of switch service disciplines
A comparison of sequential sampling models for twochoice reaction time
 Psychological Review
, 2004
"... The authors evaluated 4 sequential sampling models for 2choice decisions—the Wiener diffusion, Ornstein–Uhlenbeck (OU) diffusion, accumulator, and Poisson counter models—by fitting them to the response time (RT) distributions and accuracy data from 3 experiments. Each of the models was augmented wi ..."
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Cited by 196 (33 self)
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The authors evaluated 4 sequential sampling models for 2choice decisions—the Wiener diffusion, Ornstein–Uhlenbeck (OU) diffusion, accumulator, and Poisson counter models—by fitting them to the response time (RT) distributions and accuracy data from 3 experiments. Each of the models was augmented
PDB2PQR: an automated pipeline for the setup of Poisson–Boltzmann electrostatics calculations
 Nucleic Acids Res
, 2004
"... Continuum solvation models, such as Poisson– Boltzmann and Generalized Born methods, have become increasingly popular tools for investigating the influence of electrostatics on biomolecular structure, energetics and dynamics. However, the use of such methods requires accurate and complete structural ..."
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Cited by 95 (3 self)
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Continuum solvation models, such as Poisson– Boltzmann and Generalized Born methods, have become increasingly popular tools for investigating the influence of electrostatics on biomolecular structure, energetics and dynamics. However, the use of such methods requires accurate and complete
2. The PoissonBoltzmann equation
"... 3. Generalized Born approximations 4. Electrostatic surface forces in variational solvation ..."
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3. Generalized Born approximations 4. Electrostatic surface forces in variational solvation
The 2D Poisson Problem
"... y j ) \Gamma 2u(x i ; y j ) + u(x i\Gamma1 ; y j ) h 2 + u(x i ; y j+1 ) \Gamma 2u(x i ; y j ) + u(x i ; y j \Gamma1 ) h 2 = f(x i ; y j ) (3) at each point (x i ; y j ) of the mesh. To simplify rest of the discussion, we will replace u(x i ; y j ) by u i;j . Mathematics and Computer Scienc ..."
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y j ) \Gamma 2u(x i ; y j ) + u(x i\Gamma1 ; y j ) h 2 + u(x i ; y j+1 ) \Gamma 2u(x i ; y j ) + u(x i ; y j \Gamma1 ) h 2 = f(x i ; y j ) (3) at each point (x i ; y j ) of the mesh. To simplify rest of the discussion, we will replace u(x i ; y j ) by u i;j . Mathematics and Computer
Results 1  10
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232,707