Results 211 to 220 of about 267,629 (319)

Estimation of Change Point in Poisson Random Variables Using the Maximum Likelihood Method [PDF]

, 2016
Shalyne Nyambura
openalex   +1 more source

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

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, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

Evaluation of spatial variation in chronic wasting disease risk with Bayesian Poisson log-Gaussian model. [PDF]

Front Vet Sci
Raghavan RK, Osei FB, Stein A, Hesting S, Jaster L, Hatuwal B, Mosley JE, Raghavan A.   +7 more
europepmc   +1 more source

An Elegant Method for Generating Multivariate Poisson Random Variable [PDF]

, 2007
Inbal Yahav, Galit Shmueli
openalex   +1 more source

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, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Estimation of discrete mixed Poisson-Erlang distribution with applications to medical data. [PDF]

PLoS One
Mosilhy MA, Aljeddani SMA, Abu-Moussa MH.   +2 more
europepmc   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Statistically principled feature selection for single cell transcriptomics. [PDF]

BMC Bioinformatics
Dollinger EP, Silkwood K, Atwood S, Nie Q, Lander AD.   +4 more
europepmc   +1 more source

A non-uniform bound on Poisson approximation fora sum of negative binomial random variables

, 2017
K. Teerapabolarn
openalex   +2 more sources