Results 11 to 20 of about 33,003,501 (342)
Hierarchical models as marginals of hierarchical models [PDF]
International Journal of Approximate Reasoning, 2015 We investigate the representation of hierarchical models in terms of marginals of other hierarchical models with smaller interactions. We focus on binary variables and marginals of pairwise interaction models whose hidden variables are conditionally ...
Guido Montúfar, J. Rauh
semanticscholar +6 more sources
On Invariance in Hierarchical Models.
, 2009 A goal of central importance in the study of hierarchical models for object recognition -- and indeed the visual cortex -- is that of understanding quantitatively the trade-off between invariance and selectivity, and how invariance and discrimination properties contribute towards providing an improved representation useful for learning from data.
Jake V. Bouvrie +2 more
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Alignment-based conformance checking of hierarchical process models [PDF]
, 2023 Process mining has received much attention in the field of business pro cess management. Event logs that are generated from information systems can be correlated with the process models for conformance checking.
Wang, L +4 more
core +1 more source
Hierarchical Configuration Model [PDF]
Internet Mathematics, 2017 23 pages, 11 ...
van der Hofstad, R. +2 more
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Are There Reliable Qualitative Individual Difference in Cognition?
Journal of Cognition, 2021 In this paper we propose a new set of questions that focus on the direction of effects. In almost all studies the direction is important. For example, in a Stroop task we expect responses to incongruent items to be slower than those to congruent ones ...
Jeffrey Rouder, Julia M. Haaf
doaj +1 more source
An introduction to Bayesian inference in gravitational-wave astronomy: Parameter estimation, model selection, and hierarchical models [PDF]
Publications Astronomical Society of Australia, 2018 This is an introduction to Bayesian inference with a focus on hierarchical models and hyper-parameters. We write primarily for an audience of Bayesian novices, but we hope to provide useful insights for seasoned veterans as well.
E. Thrane, C. Talbot
semanticscholar +1 more source
Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles [PDF]
International Conference on Machine Learning, 2023 Modern hierarchical vision transformers have added several vision-specific components in the pursuit of supervised classification performance. While these components lead to effective accuracies and attractive FLOP counts, the added complexity actually ...
Chaitanya K. Ryali +12 more
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Cobaya: code for Bayesian analysis of hierarchical physical models [PDF]
Journal of Cosmology and Astroparticle Physics, 2020 We present , a general-purpose Bayesian analysis code aimed at models with complex internal interdependencies. Without the need for specific code by the user, interdependencies between different stages of a model pipeline are exploited for sampling ...
J. Torrado, A. Lewis
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Journal of the Royal Statistical Society Series B: Statistical Methodology, 1993 SUMMARY An analysis of a time series of cross-sectional data is considered under a Bayesian perspective. Information is modelled in terms of prior distributions and stratified parametric linear models developed by Lindley and Smith and dynamic linear models developed by Harrison and Stevens are merged into a general framework.
Gamerman, Dani, Migon, Hélio S.
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Data Analysis Using Regression and Multilevel/Hierarchical Models
, 2009 There is a lot of books, user manual, or guidebook that related to Data Analysis Using Regression And Multilevel Hierarchical Models PDF, such as : alternative medicine resource guide toyota conquest workshop manual mendelian patterns of inheritance ...
J. Hilbe
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