Zobrazeno 1 - 10
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pro vyhledávání: '"R. Wesley Henderson"'
Autor:
R. Wesley Henderson, Paul M. Goggans
Publikováno v:
Proceedings, Vol 33, Iss 1, p 9 (2019)
We present a novel implementation of the adaptively annealed thermodynamic integration technique using Hamiltonian Monte Carlo (HMC). Thermodynamic integration with importance sampling and adaptive annealing is an especially useful method for estimat
Externí odkaz:
https://doaj.org/article/a2fdf9b38e1f4ff98d6e2ffc53241b87
Publikováno v:
Digital Signal Processing. 70:84-93
Model comparison problems arise in many fields of science and engineering, including signal processing. In these problems, we wish to quantify how well each of a set of possible models describes a set of observations. Many numerical techniques exist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8718822dc206e42efca30c5bfc2e4f98
https://doi.org/10.1016/j.dsp.2017.07.021
https://doi.org/10.1016/j.dsp.2017.07.021
Autor:
R. Wesley Henderson, Paul M. Goggans
Publikováno v:
Entropy
Volume 21
Issue 12
Volume 21
Issue 12
We present a novel implementation of the adaptively annealed thermodynamic integration technique using Hamiltonian Monte Carlo (HMC). Thermodynamic integration with importance sampling and adaptive annealing is an especially useful method for estimat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0c2ed9dd9c6cb937b1ed0c8f595833e
Autor:
Paul M. Goggans, R. Wesley Henderson
Publikováno v:
Proceedings, Vol 33, Iss 1, p 9 (2019)
We present a novel implementation of the adaptively annealed thermodynamic integration technique using Hamiltonian Monte Carlo (HMC). Thermodynamic integration with importance sampling and adaptive annealing is an especially useful method for estimat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45232a5a35624fa9a82bde2dd18095b1
https://doi.org/10.3390/proceedings2019033009
https://doi.org/10.3390/proceedings2019033009
Autor:
R. Wesley Henderson, Paul M. Goggans
Publikováno v:
Springer Proceedings in Mathematics & Statistics ISBN: 9783319911427
BayeSys is an MCMC-based program that can be used to perform Bayesian model comparison for problems with atomic models. To sample distributions with more than one parameter, BayeSys uses the Hilbert curve to index the multidimensional parameter space
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7589ab6a455d8b4869c511bf7227c4c5
https://doi.org/10.1007/978-3-319-91143-4_28
https://doi.org/10.1007/978-3-319-91143-4_28
Autor:
R. Wesley Henderson, Paul M. Goggans
Publikováno v:
AIP Conference Proceedings.
Loudspeaker design requires accurate models of driver voice coil impedance. This paper examines three model classes (standard, Leach, and van Maanen) from the audio literature and compares them using Bayesian model comparison via nested sampling. Dat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef47bbc308d59f8d55c37afa5c267153
https://doi.org/10.1063/1.4985355
https://doi.org/10.1063/1.4985355
Publikováno v:
AIP Conference Proceedings.
This paper presents a method for designing intermodal freight rail-to-highway terminals using Bayesian model selection. Each model consists of a unique network of cities and rail terminals. The model parameters are the amount of freight flowing on ea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2f3c170fa47b05d3125da68667de41e
https://doi.org/10.1063/1.4903724
https://doi.org/10.1063/1.4903724
Publikováno v:
AIP Conference Proceedings.
This paper examines the problem of assigning a prior pdf for N positive parameters z = {z1,z2,⋯,zN} that are dependent in such a way that their sum is bounded by a known constant. It also derives a set of functions that map N independent and unifor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::518f885105a5bf26d91059c4e92fe605
https://doi.org/10.1063/1.4903716
https://doi.org/10.1063/1.4903716
Autor:
R. Wesley Henderson, Paul M. Goggans
Publikováno v:
AIP Conference Proceedings.
One of the important advantages of nested sampling as an MCMC technique is its ability to draw representative samples from multimodal distributions and distributions with other degeneracies. This coverage is accomplished by maintaining a number of so
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::842f14ace3a9f6ab6695028d5422c833
https://doi.org/10.1063/1.4903717
https://doi.org/10.1063/1.4903717
Conference
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