Results 71 to 80 of about 63,287 (274)
VIP - Variational Inversion Package with example implementations of Bayesian tomographic imaging
SeismicaBayesian inference has become an important methodology to solve inverse problems and to quantify uncertainties in their solutions. Variational inference is a method that provides probabilistic, Bayesian solutions efficiently by using optimisation.
Xin Zhang, Andrew Curtis
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Variational Bayesian Personalized Ranking
IEEE Transactions on Pattern Analysis and Machine IntelligencePairwise learning underpins implicit collaborative filtering, yet its effectiveness is often hindered by sparse supervision, noisy interactions, and popularity-driven exposure bias. In this paper, we propose Variational Bayesian Personalized Ranking (VarBPR), a tractable variational framework for implicit-feedback pairwise learning that offers ...
Bin Liu 0076 +9 more
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Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
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Variational Bayesian Monte Carlo
CoRR, 2018 In Advances in Neural Information Processing Systems 31 (NeurIPS 2018), pp. 8222-8232. (25 pages, 9 figures)
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An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials
Advanced Engineering Materials, EarlyView.An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut +16 more
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Active Learning‐Accelerated Discovery of Fibrous Hydrogels with Tissue‐Mimetic Viscoelasticity
Advanced Functional Materials, EarlyView.Active learning accelerates the design of fibrous hydrogels that mimic the viscoelasticity of native tissues. By integrating multi‐objective optimization and closed‐loop experimentation, this approach efficiently identifies optimal formulations from thousands of possibilities and decouples elasticity and viscosity. The resulting hydrogels offer tunable
Zhengkun Chen +11 more
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Sensors, 2019 In maneuvering target tracking applications, the performance of the traditional interacting multiple model (IMM) filter deteriorates seriously under heavy-tailed measurement noises which are induced by outliers.
Dong Li, Jie Sun
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An Adaptive Filter for Nonlinear Multi-Sensor Systems with Heavy-Tailed Noise
Sensors, 2020 Aiming towards state estimation and information fusion for nonlinear systems with heavy-tailed measurement noise, a variational Bayesian Student’s t-based cubature information filter (VBST-CIF) is designed.
Xiangxiang Dong, Luigi Chisci, Yunze Cai
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Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
Xibei Gongye Daxue XuebaoTo address the difficulty of obtaining high fidelity flow field information for unmanned underwater vehicle pump-jet propulsor, the accuracy of super-resolution flow field reconstruction by using a hybrid down-sampling skip connection/multi-scale ...
ZHANG Yong +4 more
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