Results 121 to 130 of about 396,010 (290)

Measurement noise covariance estimation in Gaussian filters: an online Bayesian solution

EURASIP Journal on Advances in Signal Processing
Gaussian filtering provides a Bayesian approach to dynamic state estimation, but requires precise statistical information about observation noise. When this information is unavailable, it is necessary to estimate the measurement noise covariance based on
Gerald LaMountain, Jordi Vilà-Valls, Pau Closas   +2 more
doaj   +1 more source

Forecasting using Bayesian and Information Theoretic Model Averaging: An Application to UK Inflation [PDF]

In recent years there has been increasing interest in forecasting methods that utilise large datasets, driven partly by the recognition that policymaking institutions need to process large quantities of information.
George Kapetanios, Simon Price, Vincent Labhard   +2 more
core  

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Maximin and Bayesian optimal designs for regression models [PDF]

For many problems of statistical inference in regression modelling, the Fisher information matrix depends on certain nuisance parameters which are unknown and which enter the model nonlinearly.
Dette, Holger, Haines, Linda M., Imhof, Lorens A.   +2 more
core  

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

The Sequencing Problem in Sequential Investigation Processes [PDF]

Many decision problems in various fields of application can be characterized as diagnostic problems trying to assess the true state (of the world) of given cases.
Jürgen-Peter Kretschmer
core  

Deciphering the Evolution Pattern of Structural Variations Overlapped With Repetitive Sequence During Cattle Evolution

Advanced Science, EarlyView.
The authors complement bovine pan‐SV with massive novel structural variations (SVs) identified through long‐read sequencing of 83 globally distributed cattle breeds. Repetitive sequence‐mediated SVs (rep‐SV) exhibit distinct dynamic patterns throughout cattle sub‐speciation and/or domestication processes, including uneven distribution between chr‐X and
Zhifan Guo, Jinxiu Li, Adeniyi C. Adeola, Xueyan Jiang, Juntao Ma, Jian Xiao, Dexiang Hu, Kaixing Qu, Haihong Wu, Junren Chen, Zhanxing He, Tingting Yin, Ali Esmailizadeh, Jing Luo, Olivier Hanotte, Ya‐Ping Zhang, Yan Li   +16 more
wiley   +1 more source

PREDICTIVE INFORMATION CRITERIA FOR BAYESIAN NONLINEAR REGRESSION MODELS

PREDICTIVE INFORMATION CRITERIA FOR BAYESIAN NONLINEAR REGRESSION MODELS
Bayesian nonlinear regression modeling based on basis expansions provides efficient methods for analyzing data with complicated structure. A crucial issue in the model building process is the choice of adjusted parameters including hyper-parameters for prior distribution and the number of basis functions.
openaire   +1 more source

Soft Robotics and Advanced Technologies for Minimally Invasive Bioprinting: The Future of Internal Organ Repair

Advanced Science, EarlyView.
This review examines the evolution of bioprinting toward minimally invasive in situ strategies for internal organ regeneration. It defines the technological roadmap from handheld systems to advanced minimally invasive bioprinting platforms, positioning soft robotics as a core enabler.
Duc Tu Vu, Nhu An Phan, Sy Trung Ngo, Minh Tri Phan, Thanh‐An Truong, Chi Cong Nguyen, Phuoc Thien Phan, Hoang‐Phuong Phan, Thanh Nho Do, Mai Thanh Thai   +9 more
wiley   +1 more source

Combining Bayesian Networks and MCDA methods to maximise information gain during reconnaissance in emergency situations

Journal of Safety Science and Resilience
In the immediacy of an event that disrupts the operation of an infrastructure, the time between its occurrence and the arrival of qualified personnel for emergency response can be valuable.
Daniel Lichte
doaj   +1 more source