Variational inference is a family of optimisation-based methods for approximating complex posterior distributions in Bayesian models. By transforming inference into an optimisation problem, these ...

Abstract: Methods based on variational bayes theorytare widely used to detect community structures in networks. In recent years, many related methods have emerged that provide valuable insights into ...

Abstract: Motivated by the maneuvering target tracking with sensors such as radar and sonar, this article considers the joint and recursive estimation of the dynamic state and the time-varying process ...

Multiple-timepoint arterial spin labelling MRI is a non-invasive imaging technique that permits measurement of both cerebral blood flow and arterial transit time, the latter of which is an emerging ...

Code to reproduce results in Ziyi Yin, Rafael Orozco, Felix J. Herrmann, "WISER: Multimodal variational inference for full-waveform inversion without dimensionality reduction", published in Geophysics ...

We propose an approach for joint trajectory analysis of multiple single-cell sequencing data, combining Bayesian hierarchical models with variational autoencoders. Based on a coherent statistical ...

This repository contains the official implementation of Variational Information Inference: An Interpretable Disentangled Transfer Learning Quality Prediction for Multirate Industrial Processes (TCYB ...