Results 71 to 80 of about 99,191 (258)
Inference in Bayesian Networks.
A Bayesian network is a compact, expressive representation of uncertain relationships among parameters in a domain. In this article, I introduce basic methods for computing with Bayesian networks, starting with the simple idea of summing the probabilities of events of interest. The article introduces major current methods for exact computation, briefly
openaire +2 more sources
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Mixed effects model combines fixed effects and random effects, allowing for the analysis of data with both fixed and random variations. This modeling approach is widely utilized across various fields.
Asysta Amalia Pasaribu +2 more
doaj +1 more source
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Consensus Formation and Change are Enhanced by Neutrality
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag +3 more
wiley +1 more source
Exact Inference with Approximate Computation for Differentially Private Data via Perturbations
This paper discusses how two classes of approximate computation algorithms can be adapted, in a modular fashion, to achieve exact statistical inference from differentially private data products.
Ruobin Gong
doaj
Variational Bayesian Sparse Signal Recovery With LSM Prior
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 +3 more
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Prior Expectations Bias Confidence Judgments Through Parietal Alpha‐Band Modulation
ABSTRACT Humans possess the metacognitive ability to estimate the likely accuracy of their own decisions through confidence judgments. Yet, whether prior information shapes confidence and the neural mechanisms mediating such influence, remain to be determined.
Luca Tarasi +4 more
wiley +1 more source
Single‐cell longitudinal profiling reveals that androgen‐deprivation therapy induces a DPT+ fibroblast‐complement axis that suppresses macrophage inflammation and drives CD8+ T cell exhaustion in prostate cancer. Concurrently, resistant epithelial subpopulations persist and engage TSPAN1‐ and NRXN1‐mediated programs promoting CRPC and neuroendocrine ...
Yang Chen +19 more
wiley +1 more source

