Results 91 to 100 of about 147,580 (306)

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

Approximate Bayesian Inference Based on Expected Evaluations [PDF]

, 2023
Approximate Bayesian computing (ABC) and Bayesian Synthetic likelihood (BSL) are two popular families of methods to evaluate the posterior distribution when the likelihood function is not available or tractable.
Hammer, Hugo Lewi, Riegler, Michael
core  

Natural Variation of NAR5 Determines Nitrogenase Activity and the Yield in Soybean

Advanced Science, EarlyView.
This study identified NAR5, a gene encoding a subtilisin‐like protease, that regulates nitrogenase activity in soybean nodules. Overexpressing NAR5 delayed nodule senescence, enhancing nitrogenase activity, yield, and low‐nitrogen tolerance. The elite haplotype NAR5HapI‐1 linked to superior nitrogenase activity and greater seed weight has been ...
Chao Ma, Hanyu Zhao, Haojie Feng, Xulun Dong, Lin Chen, Mingliang Yang, Runyi Chen, Chengjun Lei, Chunyan Liu, Qingshan Chen, Dawei Xin, Jinhui Wang   +11 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

Bayesian Inference and Fuzzy Information

, 2018
In standard Bayesian inference, a-priori distributions are standard probability distributions. Bayes´ theorem formulates the transition from the a-priori distribution of the stochastic quantity, which describes the parameter of interest, to the a ...
Sunanta, Owat, Viertl, Reinhard
core  

Comparative Oligo‐FISH Mapping Illuminates Chromosomal Evolution Among Rutaceae Species Diverged Over 50 Million Years

Advanced Science, EarlyView.
Oligonucleotide‐based fluorescence in situ hybridization probes were developed in the model citrus species Citrus maxima. These probes were applied to comparative karyotyping across 14 species in the Rutaceae family. This analysis revealed chromosomal evolution in lineages that diverged from Citrus nearly 52 million years ago.
Li He, Hainan Zhao, Xiaoxue Zeng, Zujun Yang, Wenting Li, Guoyan Zhang, Guangrong Li, Jian He, Bin Guan, Jiming Jiang   +9 more
wiley   +1 more source

Bayesian Inference in Dynamic Disequilibrium Models : an Application to the Polish Credit Market [PDF]

We review Bayesian inference for dynamic latent variable models using the data augmentation principle. We detail the difficulties of stimulating dynamic latent variables in a Gibbs sampler.
Luc, BAUWENS, Michel, LUBRANO
core  

Causal network inference using biochemical kinetics [PDF]

, 2014
Motivation: Networks are widely used as structural summaries of biochemical systems. Statistical estimation of networks is usually based on linear or discrete models.
Bayani, Nora, Mukherjee, Sach, Dondelinger, Frank, Bayani, N, Korkola, J, Dondelinger, F, Mukherjee, S, Oates, Chris J., Gray, JW, Korkola, James, Gray, Joe W., Oates, CJ   +11 more
core   +1 more source

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

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