Results 61 to 70 of about 33,003,501 (342)

Bottom-up learning of hierarchical models in a class of deterministic POMDP environments

International Journal of Applied Mathematics and Computer Science, 2015
The theory of partially observable Markov decision processes (POMDPs) is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the ...
Itoh Hideaki, Fukumoto Hisao, Wakuya Hiroshi, Furukawa Tatsuya   +3 more
doaj   +1 more source

Mathematical modelling of tissue formation on the basis of ordinary differential equations

Vestnik Samarskogo Gosudarstvennogo Tehničeskogo Universiteta. Seriâ: Fiziko-Matematičeskie Nauki, 2017
A mathematical model is proposed for describing the population dynamics of cellular clusters on the basis of systems of the first-order ordinary differential equations.
Maxim N Nazarov
doaj   +1 more source

Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry

FEBS Letters, EarlyView.
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri, Ayaka Nagasato‐Ichikawa, Keita Iida, Shuhei Kimura, Akira Imamoto, Mariko Okada   +5 more
wiley   +1 more source

Monitoring Animal Populations With Cameras Using Open, Multistate, N‐Mixture Models

Ecology and Evolution
Remote cameras have become a mainstream tool for studying wildlife populations. For species whose developmental stages or states are identifiable in photographs, there are opportunities for tracking population changes and estimating demographic rates ...
Alexej P. K. Sirén, Michael T. Hallworth, Jillian R. Kilborn, Chris A. Bernier, Nicholas L. Fortin, Katherina D. Geider, Riley K. Patry, Rachel M. Cliché, Leighlan S. Prout, Suzanne J. Gifford, Scott Wixsom, Toni Lyn Morelli, Tammy L. Wilson   +12 more
doaj   +1 more source

Bayesian Hierarchical Random Effects Models in Forensic Science

Frontiers in Genetics, 2018
Statistical modeling of the evaluation of evidence with the use of the likelihood ratio has a long history. It dates from the Dreyfus case at the end of the nineteenth century through the work at Bletchley Park in the Second World War to the present day.
Colin G. G. Aitken
doaj   +1 more source

Hierarchical generalized additive models in ecology: an introduction with mgcv

PeerJ, 2019
In this paper, we discuss an extension to two popular approaches to modeling complex structures in ecological data: the generalized additive model (GAM) and the hierarchical model (HGLM).
Eric J. Pedersen, David L. Miller, G. Simpson, Noam Ross   +3 more
semanticscholar   +1 more source

Fast moment‐based estimation for hierarchical models [PDF]

, 2015
Hierarchical models allow for heterogeneous behaviours in a population while simultaneously borrowing estimation strength across all subpopulations. Unfortunately, existing likelihood‐based methods for fitting hierarchical models have high computational ...
Patrick O. Perry
semanticscholar   +1 more source

Learning hierarchical models of activity [PDF]

2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), 2005
This paper investigates learning hierarchical statistical activity models in indoor environments. The abstract hidden Markov model (AHMM) is used to represent behaviors in stochastic environments. We train the model using both labeled and unlabeled data and estimate the parameters using expectation maximization (EM). Results are shown on three datasets:
Sarah Osentoski, Victoria Manfredi, Sridhar Mahadevan   +2 more
openaire   +1 more source

Artificial molecular machines and motors—Design and control of nanoscale motion

FEBS Letters, EarlyView.
Molecules are constantly moving because of thermal fluctuations, but random motion alone cannot be exploited to perform directional tasks. Artificial molecular machines use chemical, electrical, or light energy to bias this motion. Molecular shuttles, rotary motors, and supramolecular pumps illustrate how nanoscale movement can be controlled and ...
Leonardo Andreoni, Alberto Credi
wiley   +1 more source

Morphological variance in cave and surface populations of Asellus aquaticus challenges the fluctuating selection and greater male variability hypotheses

Frontiers in Ecology and Evolution
IntroductionFluctuating selection, the changes in the strength and/or direction of natural selection stemming from fine-scale spatio-temporal environmental variation, is a fundamental, yet rarely tested explanation for the maintenance of phenotypic ...
Anna Biró, Anna Biró, Anna Biró, Gergely Balázs, Gergely Balázs, Gergely Horváth, Gergely Horváth, Žiga Fišer, Cene Fišer, Serban M. Sarbu, Serban M. Sarbu, Gábor Herczeg, Gábor Herczeg   +12 more
doaj   +1 more source