Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Natchanon Suaysom"'
Publikováno v:
Involve 12, no. 5 (2019), 737-754
Determining how the brain stores information is one of the most pressing problems in neuroscience. In many instances, the collection of stimuli for a given neuron can be modeled by a convex set in $\mathbb{R}^d$. Combinatorial objects known as \emph{
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::579113b12e762bbbd6769e613cccf014
https://doi.org/10.2140/involve.2019.12.737
https://doi.org/10.2140/involve.2019.12.737
Publikováno v:
Physical Review D, vol 103, iss 3
Physical Review
Physical Review
Histogram-based template fits are the main technique used for estimating parameters of high energy physics Monte Carlo generators. Parametrized neural network reweighting can be used to extend this fitting procedure to many dimensions and does not re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd62672ed328332b80575bb1a4dfa062
https://escholarship.org/uc/item/4sp8m9kq
https://escholarship.org/uc/item/4sp8m9kq
Autor:
Matthew Lorig, Natchanon Suaysom
We derive an explicit asymptotic approximation for the implied volatilities of Call options written on bonds assuming the short-rate is described by an affine short-rate model. For specific affine short-rate models, we perform numerical experiments i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a76af12bd298c2eee9b7a298e7bb4504
Autor:
Natchanon Suaysom
In this paper, we propose a novel algorithm that rearrange the topic assignment results obtained from topic modeling algorithms, including NMF and LDA. The effectiveness of the algorithm is measured by how much the results conform to expert opinion,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::684e1555e018cbaba3da651b5cfbcf6f
Autor:
Jeffrey Krupa, Maria Acosta Flechas, Kelvin Lin, Jack Dinsmore, Javier Duarte, Scott Hauck, Nhan Tran, Burt Holzman, Natchanon Suaysom, Mia Liu, Thomas Klijnsma, Kevin Pedro, Philip Harris, Dylan Rankin, Matthew Trahms, Shih-Chieh Hsu
Publikováno v:
Machine Learning: Science and Technology. 2:035005
In the next decade, the demands for computing in large scientific experiments are expected to grow tremendously. During the same time period, CPU performance increases will be limited. At the CERN Large Hadron Collider (LHC), these two issues will co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::83450aa7b31930901db6da559af4eacb
https://doi.org/10.1088/2632-2153/abec21
https://doi.org/10.1088/2632-2153/abec21
Autor:
Natchanon Suaysom, Weiqing Gu
Publikováno v:
SSRN Electronic Journal.
In this paper, we propose a novel algorithm that rearrange the topic assignment results obtained from topic modeling algorithms, including NMF and LDA. The effectiveness of the algorithm is measured by how much the results conform to expert opinion,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c3deadb017e2dfdac0eb5a7f005e816
https://doi.org/10.2139/ssrn.3414903
https://doi.org/10.2139/ssrn.3414903