The paper presents a Bayesian framework for the calibration of financial models using neural stochastic differential equations (neural SDEs), for which we also formulate a global universal ...

ABSTRACT: Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and ...

Recent advancements in astrophysical observations of compact stars, particularly the new and updated NICER constraints, have provided mass-radius (M-R) data for pulsars spanning masses from 1 to 2 M ⊙ ...

The Bayesian structural equation model integrates the principles of Bayesian statistics, providing a more flexible and comprehensive modeling framework. In exploring complex relationships between ...

To create a conda environment mpe with all necessary dependencies run: conda env create --file environment.yml We use torch 2.2.1 with cuda 12.1.1 In the following we provide exemplary commands for ...

Abstract: Gene regulatory networks (GRNs) are underlying networks identified by interactive relationships between genes. Reconstructing GRNs from massive genetic data is important for understanding ...

Abstract: Equation-informed neural networks (EINS) method provides an efficient way for the coefficient extraction of the complicated empirical function from large observation data. The Bayesian ...

This paper presents a computationally efficient framework for identifying resonance modes of 3D radio-frequency (RF) cavities with damping waveguide ports. The proposed framework relies on surface ...

Read the Reflection, written 8 August 2021, below the following original Transmission. Human society has a lot of very, very hard decisions to make in the days ahead. These will require us to make a ...

1 Respiratory Medicine Department, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland 2 University Center for Primary Care and Public Health (Unisanté), DFRI/Division of ...