Results 71 to 80 of about 50,616 (261)

Bayesian Prior Choice in IRT estimation using MCMC and Variational Bayes

Frontiers in Psychology, 2016
This study investigated the impact of three prior distributions: matched, standard vague, and hierarchical in Bayesian estimation parameter recovery in two and one parameter models. Two Bayesian estimation methods were utilized: Markov chain Monte Carlo (
Prathiba Natesan, Ratna Nandakumar, Tom Minka, Jonathan Rubright   +3 more
doaj   +1 more source

Muscle Control of an Extra Robotic Digit

Advanced Robotics Research, EarlyView.
This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ, Lucy Dowdall, Francesco Cenciarelli, Kitty Goodridge, Mabel Ziman, Hristo Dimitrov, Danielle Clode, Tamar R. Makin   +7 more
wiley   +1 more source

Steve: A Hierarchical Bayesian Model for Supernova Cosmology [PDF]

The Astrophysical Journal, 2019
Abstract We present a new Bayesian hierarchical model (BHM) named Steve for performing Type Ia supernova (SN Ia) cosmology fits. This advances previous works by including an improved treatment of Malmquist bias, accounting for additional sources of systematic uncertainty, and increasing numerical efficiency.
S. R. Hinton, T. M. Davis, A. G. Kim, D. Brout, C. B. D’Andrea, R. Kessler, J. Lasker, C. Lidman, E. Macaulay, A. Möller, M. Sako, D. Scolnic, M. Smith, R. C. Wolf, M. Childress, E. Morganson, S. Allam, J. Annis, S. Avila, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, C. E. Cunha, L. N. da Costa, C. Davis, J. De Vicente, D. L. DePoy, P. Doel, T. F. Eifler, B. Flaugher, P. Fosalba, J. Frieman, J. García-Bellido, E. Gaztanaga, D. W. Gerdes, R. A. Gruendl, J. Gschwend, G. Gutierrez, W. G. Hartley, D. L. Hollowood, K. Honscheid, E. Krause, K. Kuehn, N. Kuropatkin, O. Lahav, M. Lima, M. A. G. Maia, M. March, J. L. Marshall, F. Menanteau, R. Miquel, R. L. C. Ogando, A. A. Plazas, E. Sanchez, V. Scarpine, R. Schindler, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, M. Soares-Santos, F. Sobreira, E. Suchyta, G. Tarle, D. Thomas, V. Vikram, Y. Zhang   +68 more
openaire   +10 more sources

Single‐Cell Dissection of Therapy‐Induced Remodeling Uncovers a Fibroblast‐Driven Immunosuppressive Niche and Targetable Vulnerabilities in Lethal Prostate Cancer

Advanced Science, EarlyView.
Single‐cell longitudinal profiling reveals that androgen‐deprivation therapy induces a DPT+ fibroblast‐complement axis that suppresses macrophage inflammation and drives CD8+ T cell exhaustion in prostate cancer. Concurrently, resistant epithelial subpopulations persist and engage TSPAN1‐ and NRXN1‐mediated programs promoting CRPC and neuroendocrine ...
Yang Chen, Dandan Dong, Jinling Liao, Naikai Liao, Mengqi Liu, Qin Zhang, Siting Chen, Qi Liu, Ying Lu, Tianyu Li, Chunlin Zou, Qiong Song, Qiuyan Wang, Jian Liang, Qiji Xie, Chengyang Li, Mengyun Wang, Jiwen Cheng, Zengnan Mo, Gong‐Hong Wei   +19 more
wiley   +1 more source

A hierarchical bayesian model for size recommendation in fashion [PDF]

Proceedings of the 12th ACM Conference on Recommender Systems, 2018
We introduce a hierarchical Bayesian approach to tackle the challenging problem of size recommendation in e-commerce fashion. Our approach jointly models a size purchased by a customer, and its possible return event: 1. no return, 2. returned too small 3. returned too big. Those events are drawn following a multinomial distribution parameterized on the
Romain Guigourès, Yuen King Ho, Evgenii Koriagin, Abdul-Saboor Sheikh, Urs Bergmann, Reza Shirvany   +5 more
openaire   +2 more sources

Iron‐Mediated Release of Aged Dissolved Organic Carbon From Waterlogged Peatland Under Warming

Advanced Science, EarlyView.
This study conducts a five‐year in situ warming experiment in high‐altitude peatlands to examine dissolved organic carbon (DOC) release. The study shows that warming promotes the release of plant‐derived modern DOC in drained peatlands, but amplifies aquatic export of century‐old DOC from waterlogged peatlands via Fe‐mediated DOC mobilization—a ...
Guohua Dai, Zhiying Yang, Zongguang Liu, Wanjia Hu, Lixiao Ma, Enze Kang, Wanqing Luo, Yunpeng Zhao, Chengzhu Liu, Juan Jia, Ting Liu, Chen He, Quan Shi, Jianliang Liu, Yongheng Gao, Huai Chen, Hailong Zhang, Meixun Zhao, Xiaojuan Feng   +18 more
wiley   +1 more source

Bayesian hierarchical statistical SIRS models

Statistical Methods & Applications, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lili Zhuang, Noel Cressie
openaire   +3 more sources

MFPD: A Multiple Fungal Pathogen Detection Pipeline Across Diverse Habitats

Advanced Science, EarlyView.
The MFPD pipeline integrates a comprehensive ITS reference database of fungal pathogens, optimized parameters, and algorithms tailored for both full‐length and subregion sequences that balance accuracy and computational efficiency; it enables high‐throughput, species‐level identification from amplicon sequencing data, supporting large‐scale ...
Yi Shen, Xinrun Yang, Jiabao Yu, Yaozhong Zhang, Tianjie Yang, Yang Gao, Xiaofang Wang, Alexandre Jousset, Waseem Raza, Fang‐Jie Zhao, Qirong Shen, Gaofei Jiang, Zhong Wei, Yangchun Xu   +13 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source