Results 211 to 220 of about 43,679 (257)

LLM‐based prior elicitation for Bayesian graphical modeling

British Journal of Mathematical and Statistical Psychology, EarlyView.
ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski, Meike Waaijers, Giuseppe Arena   +2 more
wiley   +1 more source

Computational design of HLA class I superbinders for broad T cell immunogenicity. [PDF]

Proc Natl Acad Sci U S A
Peer E, Cohen-Lavi L, Sette A, Sidney J, Hertz T.   +4 more
europepmc   +1 more source

Modeling insurance claims using Bayesian nonparametric regression. [PDF]

PLoS One
Shams M, Ghosh K.
europepmc   +1 more source

Vasopressin and angiotensin II pathways differentially modulate human fear response dynamics to looming threats. [PDF]

PLoS Biol
Han M, Dong W, Fu K, Wang J, Xu Y, Zheng Y, Kendrick K, Ferraro S, Xu T, Yao D, Becker B.   +10 more
europepmc   +1 more source

Multiple model trajectory poisson multi-bernoulli mixtures filter for tracking multiple maneuvering objects. [PDF]

Sci Rep
Salim I, Okasha N, Barbary M, Anis W.
europepmc   +1 more source

Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change. [PDF]

Cell Syst
Copperman J, Mclean IC, Gross SM, Singh J, Murthy V, Chang YH, Davies AE, Zuckerman DM, Heiser LM.   +8 more
europepmc   +1 more source

Unveiling the heterogeneity of T2DM: a narrative review of clustering algorithms in stratifying comorbidity and complication risk. [PDF]

Cardiovasc Diabetol Endocrinol Rep
Aziz N, Kamran N, Almas A, Bloomfield GS, Ahmed A, Samad Z, Mahmood T.   +6 more
europepmc   +1 more source

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Markov clustering ensemble

Knowledge-Based Systems, 2022
Junwei Luo, Hongjun Wang
exaly   +2 more sources

Clustering in Block Markov Chains [PDF]

Annals of Statistics, 2020
This paper considers cluster detection in Block Markov Chains (BMCs). These Markov chains are characterized by a block structure in their transition matrix. More precisely, the $n$ possible states are divided into a finite number of $K$ groups or clusters, such that states in the same cluster exhibit the same transition rates to other states.
Jaron Sanders
exaly   +6 more sources

A Modified Markov Clustering Approach for Protein Sequence Clustering [PDF]

Lecture Notes in Computer Science, 2008
In this paper we propose a modified Markov clustering algorithm for efficient clustering of large protein sequence databases, based on previously evaluated sequence similarity criteria. The proposed alteration consists in an exponentially decreasing inflation rate, which aims at helping the quick creation of the hard structure of clusters by using a ...
László Szilágyi, Sándor M Szilágyi, Szilágyi László   +2 more
exaly   +2 more sources