Results 91 to 100 of about 1,249,090 (302)

Using Bayesian Optimization to Increase the Efficiency of III‐V Multijunction Solar Cells

Advanced Theory and Simulations, EarlyView.
Technology Computer Aided Design (TCAD) modeling is crucial for designing complex optoelectronic devices like III‐V multijunction solar cells. Bayesian optimization is proposed as a robust method to address challenges in optimizing costly black‐box TCAD solvers.
Pablo F. Palacios, Carlos Algora
wiley   +1 more source

Network Plasticity as Bayesian Inference

, 2015
General results from statistical learning theory suggest to understand not only brain computations, but also brain plasticity as probabilistic inference. But a model for that has been missing.
Habenschuss, Stefan, Kappel, David, Legenstein, Robert, Maass, Wolfgang   +3 more
core   +3 more sources

VDLIN: A Deep Learning‐Based Platform for Methylcobalamin‐Inspired Immunomodulatory Compound Screening

Advanced Science, EarlyView.
Using the convolutional neural network model VDLIN, Co7 is identified as a promising therapeutic candidate. Co7 demonstrates distinct advantages over MCB by effectively balancing anti‐inflammatory and immune‐stimulatory functions, making it a potential novel approach for immune modulation.
Xuefei Guo, Yang Zhao, Xianle Rong, Chenxi Niu, Shiyu Hu, Qiang Liu, Fuping You   +6 more
wiley   +1 more source

Variational Bayesian Sparse Signal Recovery With LSM Prior

IEEE Access, 2017
This paper presents a new sparse signal recovery algorithm using variational Bayesian inference based on the Laplace approximation. The sparse signal is modeled as the Laplacian scale mixture (LSM) prior.
Shuanghui Zhang, Yongxiang Liu, Xiang Li, Guoan Bi   +3 more
doaj   +1 more source

Construction of a Multitissue Cell Atlas Reveals Cell‐Type‐Specific Regulation of Molecular and Complex Phenotypes in Pigs

Advanced Science, EarlyView.
This research conducts an in‐depth investigation of cell‐type‐specific regulatory mechanisms underlying molecular and complex phenotypes through integrative analysis of multitissue single‐nucleus RNA sequencing, bulk RNA‐seq, and genome‐wide association study (GWAS) data in pigs.
Lijuan Chen, Houcheng Li, Jinyan Teng, Zhen Wang, Xiaolu Qu, Zhe Chen, Xiaodian Cai, Haonan Zeng, Zhonghao Bai, Jinghui Li, Xiangchun Pan, Leyan Yan, Fei Wang, Lin Lin, Yonglun Luo, Goutam Sahana, Mogens Sandø Lund, Maria Ballester, Daniel Crespo‐Piazuelo, Peter Karlskov‐Mortensen, Merete Fredholm, Alex Clop, Marcel Amills, Crystal Loving, Christopher K. Tuggle, Ole Madsen, Jiaqi Li, Zhe Zhang, George E. Liu, Jicai Jiang, Lingzhao Fang, Guoqiang Yi   +31 more
wiley   +1 more source

Bayesian Methodologies with pyhf [PDF]

EPJ Web of Conferences
bayesian_pyhf is a Python package that allows for the parallel Bayesian and frequentist evaluation of multi-channel binned statistical models. The Python library pyhf is used to build such models according to the HistFactory framework and already ...
Feickert Matthew, Heinrich Lukas, Horstmann Malin   +2 more
doaj   +1 more source

Patterns of Scalable Bayesian Inference

, 2016
Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge.
Adams, Ryan P., Angelino, Elaine, Johnson, Matthew James   +2 more
core   +1 more source

Reliable AI Platform for Monitoring BCI Caused Brain Injury and Providing Real‐Time Protection

Advanced Science, EarlyView.
BrainGuard enables real‐time and interpretable assessment of brain injury caused by brain computer interface (BCI). Using feature‐based Gaussian process (GP) emulators trained on limited biomechanical data, it efficiently predicts full‐field strain and constructs patient‐specific digital brain twins to support clinical diagnosis and long‐term BCI ...
Chufan He, Yanjun Ding, Timon Rabczuk, Chensen Ding   +3 more
wiley   +1 more source

To integrate or not to integrate: Temporal dynamics of hierarchical Bayesian causal inference.

PLoS Biology, 2019
To form a percept of the environment, the brain needs to solve the binding problem-inferring whether signals come from a common cause and are integrated or come from independent causes and are segregated.
Máté Aller, Uta Noppeney
doaj   +1 more source

CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions

Advanced Science, EarlyView.
CellPolaris decodes how transcription factors guide cell fate by building gene regulatory networks from transcriptomic data using transfer learning. It generates tissue‐ and cell‐type‐specific networks, identifies master regulators in cell state transitions, and simulates TF perturbations in developmental processes.
Guihai Feng, Xin Qin, Jiahao Zhang, Wuliang Huang, Yiyang Zhang, Wentao Cui, Yao Chen, Shirui Li, Wenhao Liu, Yao Tian, Yana Liu, Jingxi Dong, Ping Xu, Zhenpeng Man, Guole Liu, Zhongming Liang, Xinlong Jiang, Xiaodong Yang, Pengfei Wang, Ge Yang, Hongmei Wang, Xuezhi Wang, Ming‐Han Tong, Yuanchun Zhou, Shihua Zhang, Yiqiang Chen, Yong Wang, Xin Li   +27 more
wiley   +1 more source