Results 51 to 60 of about 251,998 (281)
, 2010 We derive a Poisson random field model for population site polymorphisms differences within and between two species that share a relatively recent common ancestor. The model can be either equilibrium or time inhomogeneous.
Amei, Amei, Sawyer, Stanley
core +1 more source
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
APLIKASI MARKOV RANDOM FIELD PADA MASALAH INDUSTRI
Jurnal Teknik Industri, 2002 Markov chain in the stochastic process is widely used in the industrial problems particularly in the problem of determining the market share of products.
Siana Halim
doaj
Metastates in mean-field models with random external fields generated by Markov chains [PDF]
, 2011 We extend the construction by Kuelske and Iacobelli of metastates in finite-state mean-field models in independent disorder to situations where the local disorder terms are are a sample of an external ergodic Markov chain in equilibrium. We show that for
A. Bovier +20 more
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Advanced Intelligent Discovery, EarlyView.This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla +4 more
wiley +1 more source
A Markov Random Field Model for the Restoration of Foggy Images
International Journal of Advanced Robotic Systems, 2014 This paper presents an algorithm to remove fog from a single image using a Markov random field (MRF) framework. The method estimates the transmission map of an image degradation model by assigning labels with a MRF model and then optimizes the map ...
Fan Guo, Jin Tang, Hui Peng
doaj +1 more source
Using Markov Random Field and Analytic Hierarchy Process to Account for Interdependent Criteria
Algorithms, 2023 The Analytic Hierarchy Process (AHP) has been a widely used multi-criteria decision-making (MCDM) method since the 1980s because of its simplicity and rationality.
Jih-Jeng Huang, Chin-Yi Chen
doaj +1 more source
Consistent estimation of the basic neighborhood of Markov random fields [PDF]
, 2006 For Markov random fields on $\mathbb{Z}^d$ with finite state space, we address the statistical estimation of the basic neighborhood, the smallest region that determines the conditional distribution at a site on the condition that the values at all other ...
Csiszár, Imre, Talata, Zsolt
core +4 more sources
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
Advanced Intelligent Discovery, EarlyView.The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Advanced Experiment Design Strategies for Drug Development
Advanced Intelligent Discovery, EarlyView.Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang +3 more
wiley +1 more source