Results 81 to 90 of about 1,412,360 (277)

Bootstrapping Sequential Monte Carlo Tracking [PDF]

, 2003
Sequential Monte Carlo (SMC) methods have in recent years been applied to handle some of the problems inherent to model-based tracking. In this paper we suggest to apply bootstrapping to reduce the required number of particles in SMC tracking. By bootstrapping is meant to track reliable low-level image features and use them to bootstrap the high-level ...
Thomas B. Moeslund, Erik Granum
openaire   +2 more sources

Independent Resampling Sequential Monte Carlo Algorithms [PDF]

IEEE Transactions on Signal Processing, 2017
Sequential Monte Carlo algorithms, or Particle Filters, are Bayesian filtering algorithms which propagate in time a discrete and random approximation of the a posteriori distribution of interest. Such algorithms are based on Importance Sampling with a bootstrap resampling step which aims at struggling against weights degeneracy.
Lamberti, Roland, Petetin, Yohan, Desbouvries, François, Septier, François   +3 more
openaire   +3 more sources

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Machine learning the conformal manifold of holographic CFT2’s

Journal of High Energy Physics
We investigate the structure of conformal manifolds around AdS3 × S 3 which lift from continuous flat directions in the scalar potential of gauged supergravity resulting from six-dimensional 𝒩 = (1, 1) supergravity.
Bastien Duboeuf, Camille Eloy, Gabriel Larios   +2 more
doaj   +1 more source

Sequential Monte Carlo with Highly Informative Observations [PDF]

SIAM/ASA Journal on Uncertainty Quantification, 2015
25 pages, 11 ...
del Moral, Pierre, Murray, Lawrence M.
openaire   +4 more sources

Influence of Scan Strategies in Electron Beam Powder Bed Fusion on Solidification, Microstructure, and High‐Temperature Compressive Properties of γ′‐Strengthened Inconel 738LC

Advanced Engineering Materials, EarlyView.
Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati, Karthik Kumar Banku, Prasanth Bondi, Ivan Zhirnov, Yangyiwei Yang, Gordon Schmidt, Jürgen Christen, Georg Hasemann, Manja Krüger, Bai‐Xiang Xu, Bilal Gökce, Silja‐Katharina Rittinghaus   +11 more
wiley   +1 more source

Sequential Monte Carlo for Graphical Models

, 2014
We propose a new framework for how to use sequential Monte Carlo (SMC) algorithms for inference in probabilistic graphical models (PGM). Via a sequential decomposition of the PGM we find a sequence of auxiliary distributions defined on a monotonically increasing sequence of probability spaces. By targeting these auxiliary distributions using SMC we are
Andersson Naesseth, Christian, Lindsten, Fredrik, Schön, Thomas   +2 more
openaire   +4 more sources

Robust Electrocaloric Performance Enabled by Highly‐Polar Frustrated Nanodomains in NaNbO3‐Based Ferrodistortive Relaxor

Advanced Functional Materials, EarlyView.
P4bm framework in NaNbO3‐Ba(Ti, Hf)O3 ferrodistortive relaxor entails short‐range and highly‐polar ferrodistortive orders. The abundant highly‐polar orders facilitate to increase entropy change, and robust octahedral oxygen tilt enables to impede thermal perturbations.
Feng Li, Changshun Dai, He Qi, Jiecheng Liu, Xiaoming Shi, Heng Zhou, Qiong Yang, Mingsheng Long, Lei Shan, Chunchang Wang, Jianli Wang, Zhenxiang Cheng   +11 more
wiley   +1 more source

Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference.

PLoS ONE, 2020
An important feature of Bayesian statistics is the opportunity to do sequential inference: the posterior distribution obtained after seeing a dataset can be used as prior for a second inference.
Bram Thijssen, Lodewyk F A Wessels
doaj   +1 more source

Sequential change-point detection in a multinomial logistic regression model

Open Mathematics, 2020
Change-point detection in categorical time series has recently gained attention as statistical models incorporating change-points are common in practice, especially in the area of biomedicine.
Li Fuxiao, Chen Zhanshou, Xiao Yanting
doaj   +1 more source