Results 171 to 180 of about 15,911,760 (295)

Automated White Matter Hyperintensity Segmentation Using Bayesian Model Selection: Assessment and Correlations with Cognitive Change. [PDF]

Neuroinformatics, 2020
Fiford CM, Sudre CH, Pemberton H, Walsh P, Manning E, Malone IB, Nicholas J, Bouvy WH, Carmichael OT, Biessels GJ, Cardoso MJ, Barnes J, Alzheimer’s Disease Neuroimaging Initiative.   +12 more
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Bayesian Factor Selection in Dynamic Term Structure Models [PDF]

This paper discusses Bayesian procedures for factor selection in dynamic term structure models through simulation methods based on Markov Chain Monte Carlo. The number of factors, besides influencing the fitting and prediction of observed yields, is also
Márcio Laurini
core  

Generation of Probabilistic Bits by Exploiting Orthogonal Spin Currents in Magnetic Trilayers

Advanced Science, EarlyView.
Fe/Ti/CoFeB trilayers generate orthogonal spin currents that drive stochastic spin–orbit‐torque switching for probabilistic‐bit operation. The switching probability is continuously controlled by the in‐plane magnetic field and drive current, enabling tunable random bit generation.
Donghyeon Han, Chaehyeon Shin, Seok‐Jong Kim, Yunho Jang, Daekyu Koh, Taehwan Kim, Jaeheon Jung, Geon‐Woo Baek, Minseok Kang, Eunseok Kim, Geun‐Hee Lee, Jeongchun Ryu, Makoto Kohda, Junsaku Nitta, Kab‐Jin Kim, Jongsun Park, Kyung‐Jin Lee, Byong‐Guk Park   +17 more
wiley   +1 more source

Bayesian sequential D-D optimal model-robust designs. [PDF]

Alphabetic optimal design theory assumes that the model for which the optimal design is derived is usually known. However in real-life applications, this assumption may not be credible, as models are rarely known in advance.
Ruggoo, A, Vandebroek, Martina
core  

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

Advanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen   +7 more
wiley   +1 more source

Bayesian Model Selection for Derived Responses. [PDF]

Stat Med
Roy B, Lesaffre E.
europepmc   +1 more source

Mechanistic Understanding of Protein–MOF Integration Through Surfactant‐Driven Interfacial Design

Advanced Science, EarlyView.
This study reveals how surfactant‐driven interfacial design governs the assembly and stability of protein@MOF composites. Using lipid‐based nonionic surfactants, we modulate protein–MOF interactions to improve encapsulation efficiency, MOF crystallization, and catalytic performance.
Ehsan Rashidniyaghi, Mohammad Khavani, Carlie Coerver, Ruibin Liang, Raheleh Ravanfar   +4 more
wiley   +1 more source

Forecast Combination and Bayesian Model Averaging - A Prior Sensitivity Analysis [PDF]

In this study the forecast performance of model averaged forecasts is compared to that of alternative single models. Following Eklund and Karlsson (2007) we form posterior model probabilities - the weights for the combined forecast - based on the ...
Feldkircher, Martin
core  

T2T Genome Assembly and Multi‐Omics Data Reveal Terrestrial Adaptation and Mucus Biosynthesis in Tropical Leatherleaf Slug (Laevicaulis alte)

Advanced Science, EarlyView.
A gap‐free genome assembly and multi‐omics comparison of the terrestrial slug Laevichaulis alte with an aquatic relative reveal that expansion of the VEGF family orchestrates mucus production, lipid metabolism, and immune defense—highlighting key molecular innovations for conquering life on land.
Gang Wang, Shaofang He, Zhongkai Wang, Aobo Pang, Xiaoli Sun, Rongchen Liu, Fang Wang, Sisi Chen, Zhijuan Bian, Dongcheng Wei, Liuhan Wu, Siyao Zhao, Qiuting Ji, Yiqi Sun, Niying Sun, Yushinta Fujaya, Boping Tang, Kianann Tan, Daizhen Zhang, Lianfu Chen   +19 more
wiley   +1 more source