Results 81 to 90 of about 557,766 (311)

Study of new rare event simulation schemes and their application to extreme scenario generation [PDF]

, 2018
This is a companion paper based on our previous work on rare event simulation methods. In this paper, we provide an alternative proof for the ergodicity of shaking transformation in the Gaussian case and propose two variants of the existing methods ...
Agarwal, Ankush, De Marco, Stefano, Gobet, Emmanuel, Liu, Gang   +3 more
core   +1 more source

Multi‐Tissue Genetic Regulation of RNA Editing in Pigs

Advanced Science, EarlyView.
This study presents the first multi‐tissue map of RNA editing and its genetic regulation in pigs. By integrating RNA editing profiles, edQTL mapping, GWAS, and cross‐species comparisons, this work establishes RNA editing as a distinct regulatory layer linking genetic variation to complex traits, highlighting its functional and evolutionary significance.
Xiangchun Pan, Wentao Gong, Xiaodian Cai, Jinyan Teng, Jiali Cai, Haonan Zeng, Wondossen Ayalew, Qingpeng Shen, Zhanming Zhong, Yifei Wang, Wenjing Zhang, Yuhan Tian, Dantong Xu, Yahui Gao, Hongwei Yin, Yuebo Zhang, Jiahui Hou, Tianru Zhou, Jiaqi Li, Lingzhao Fang, Xiaolong Yuan, Zhe Zhang   +21 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

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

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

PPM-Decay: A computational model of auditory prediction with memory decay.

PLoS Computational Biology, 2020
Statistical learning and probabilistic prediction are fundamental processes in auditory cognition. A prominent computational model of these processes is Prediction by Partial Matching (PPM), a variable-order Markov model that learns by internalizing n ...
Peter M C Harrison, Roberta Bianco, Maria Chait, Marcus T Pearce   +3 more
doaj   +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, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Gene Hunting with Knockoffs for Hidden Markov Models

, 2017
Modern scientific studies often require the identification of a subset of relevant explanatory variables, in the attempt to understand an interesting phenomenon. Several statistical methods have been developed to automate this task, but only recently has
Candès, Emmanuel J., Sabatti, Chiara, Sesia, Matteo   +2 more
core   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Labor Market Entry and Earnings Dynamics: Bayesian Inference Using Mixtures-of-Experts Markov Chain Clustering [PDF]

, 2010
This paper analyzes patterns in the earnings development of young labor market en- trants over their life cycle. We identify four distinctly di®erent types of transition patterns between discrete earnings states in a large administrative data set ...
Frühwirth-Schnatter, Sylvia, Weber, Andrea, Winter-Ebmer, Rudolf   +2 more
core  

A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes

, 2017
We propose a voxel-wise general linear model with autoregressive noise and heteroscedastic noise innovations (GLMH) for analyzing functional magnetic resonance imaging (fMRI) data.
Eklund, Anders, Lindquist, Martin A., Villani, Mattias   +2 more
core   +1 more source