Results 61 to 70 of about 54,345 (310)

MolMiner: Toward Controllable, Three‐Dimensional‐Aware, Fragment‐Based Molecular Design

Advanced Intelligent Discovery, EarlyView.
MolMiner is a fragment‐based, geometry‐aware, and order‐agnostic generative model for molecular design with strong inductive biases. Using symmetry‐aware fragment assembly, dynamic three‐dimensional geometry, and multi‐property conditioning, MolMiner enables interpretable and controllable molecular generation.
Raul Ortega‐Ochoa, Tejs Vegge, Jes Frellsen   +2 more
wiley   +1 more source

Linking community structure and climate vulnerability in desert plant assemblages of southern California

American Journal of Botany, EarlyView.
Abstract Premise Desert plant assemblages in southern California provide an opportunity to link patterns of community structure with climate‐driven vulnerability in a rapidly changing environment. California sustains an exceptionally diverse flora of approximately 4300 plant species, with 31% identified as endemic.
Hector Zumbado‐Ulate, Luis E. Barrios, Danelle A. Baronia, G. Darrel Jenerette, Lynn C. Sweet   +4 more
wiley   +1 more source

Parameter estimation for X-ray scattering analysis with Hamiltonian Markov Chain Monte Carlo

Journal of Synchrotron Radiation, 2022
Bayesian-inference-based approaches, in particular the random-walk Markov Chain Monte Carlo (MCMC) method, have received much attention recently for X-ray scattering analysis.
Zhang Jiang, Jin Wang, Matthew V. Tirrell, Juan J. de Pablo, Wei Chen   +4 more
doaj   +1 more source

Phylogenomic insights into the genus Tulipa (Liliaceae): Taxonomy, evolution, and biogeography

American Journal of Botany, EarlyView.
Abstract Premise Tulips are one of the best‐known geophytes, but their taxonomy remains convoluted and their evolutionary history poorly understood. Here, we used plastid genomes to identify some issues with current classification, understand the diversification history of the genus, and identify potential species linked to historical cultivation ...
Brett Wilson, Maarten J. M. Christenhusz, Nathanael Walker‐Hale, Natalya Beshko, Mariyo Boboev, Colin Clubbe, Davron Dekhkonov, Aibek Dolotbakov, Mehmet Firat, Thomas Freeth, Sjaak de Groot, Avni Hajdari, Georgy A. Lazkov, Ormon Sultangaziev, Komiljon S. Tojibaev, Ben J. M. Zonneveld, Kaiyrkul T. Shalpykov, Samuel F. Brockington   +17 more
wiley   +1 more source

sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo

Journal of Statistical Software, 2019
This paper introduces the R package sgmcmc; which can be used for Bayesian inference on problems with large data sets using stochastic gradient Markov chain Monte Carlo (SGMCMC).
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth   +3 more
doaj   +1 more source

MCMC-Driven Learning

This paper is intended to appear as a chapter for the Handbook of Markov Chain Monte Carlo. The goal of this chapter is to unify various problems at the intersection of Markov chain Monte Carlo (MCMC) and machine learning$\unicode{x2014}$which includes black-box variational inference, adaptive MCMC, normalizing flow construction and transport-assisted ...
Alexandre Bouchard-Côté, Trevor Campbell, Geoff Pleiss, Nikola Surjanovic   +3 more
openaire   +2 more sources

Place‐based risk: Examining relationships between adolescent perceptions of community risk factors and adolescent substance use across geographic contexts

American Journal of Community Psychology, EarlyView.
Abstract Mixed evidence for the influence of structural and social factors on adolescent substance use behaviors exists across the rural–urban continuum. Therefore, this study explores how adolescent perceptions of structural and social community risk factors are associated with lifetime and past 30‐day use of alcohol, marijuana, cigarettes, and ...
Melissa Pearman Fenton, Sarah D. Lynne, Josie L. Bryan, Catherine Woodstock Striley, Larry F. Forthun   +4 more
wiley   +1 more source

Credit risk clustering in a business group: Which matters more, systematic or idiosyncratic risk?

Cogent Economics & Finance, 2019
Understanding how defaults correlate across firms is a persistent concern in risk management. In this paper, we apply covariate-dependent copula models to assess the dynamic nature of credit risk dependence, which we define as “credit risk clustering ...
Feng Li, Zhuojing He
doaj   +1 more source

Becoming resilient: Community‐driven change and the civic capacity index

American Journal of Community Psychology, EarlyView.
Abstract One of the principal features of successful community governance is that it is collaborative and thus dependent on a community's ability to work together. However, there are no valid, comprehensive means to assess a community's capacity to respond to civic challenges in collaborative ways, and that are predictive of community resilience and ...
David MacPhee, David Chrislip, Patti Schmitt   +2 more
wiley   +1 more source

Bayesian parameter inference by Markov chain Monte Carlo with hybrid fitness measures: theory and test in apoptosis signal transduction network. [PDF]

PLoS ONE, 2013
When model parameters in systems biology are not available from experiments, they need to be inferred so that the resulting simulation reproduces the experimentally known phenomena. For the purpose, Bayesian statistics with Markov chain Monte Carlo (MCMC)
Yohei Murakami, Shoji Takada
doaj   +1 more source