Abstract: Time-frequency (TF) analysis is a useful tool for seismic data processing and interpretation. We introduce sparse Bayesian learning (SBL) to TF analysis and propose a new SBL-based ...

Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...

Clinical trials for a new drug can take years to complete, and cost up to hundreds of millions of dollars. New draft guidance from the U.S. Food and Drug Administration aims to make that process ...

Abstract: Effective state assessment of equipment can provide guarantees for the safe and stable operation of the power grid. To solve the problem of inaccurate evaluation results of transmission ...

The typical participant is a PhD student in Statistics or related fields (Mathematical Statistics, Engineering Science, Quantitative Finance, Computer Science, ...). The participants are expected to ...

PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference, previously implemented in MATLAB. VBMC is an approximate inference method ...

Copyright: © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Frequentist and Bayesian ...

The introduction of ”two-dimensional” (2D) nuclear magnetic resonance (NMR) spectroscopy in the mid-1970s is generally accepted to be a defining advance in modern NMR analysis. This was the work of ...

p-values are commonly used as summaries of evidence for association between a genetic variant and phenotype, but they have an important limitation in that they are unable to quantify how confident one ...

Bayesian Decision Trees provide a probabilistic framework that reduces the instability of Decision Trees while maintaining their explainability. While Markov Chain Monte Carlo methods are typically ...