Results 111 to 120 of about 725,754 (336)
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
The Representation of Social Processes by Markov Models [PDF]
, 1976 Burton H. Singer, Seymour Spilerman
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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
On Markov Chain Modeling to Some Weather Data [PDF]
, 1976 Phillip E. Gates, Howell Tong
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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
Bayes estimates of Markov trends in possibly cointegrated series: an application to US consumption and income [PDF]
Stylized facts show that average growth rates of US per capita consumption and income differ in recession and expansion periods. Since a linear combination of such series does not have to be a constant mean process, standard cointegration analysis ...
Dijk, H.K. van, Paap, R.
core +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
Signal recognition models compared for random and Markov presentation sequences [PDF]
, 1971 Arthur Sandusky
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Estimating Components in Finite Mixtures and Hidden Markov Models [PDF]
When the unobservable Markov chain in a hidden Markov model is stationary the marginal distribution of the observations is a finite mixture with the number of terms equal to the number of the states of the Markov chain.
D.S. Poskitt, Jing Zhang
core
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai +3 more
wiley +1 more source