While the choice of prior is one of the most critical parts of the Bayesian inference workflow,
recent Bayesian deep learning models have often fallen back on vague priors, such as …

Purpose This paper contributes to the literature by discussing the impact of machine
learning (ML) on management accounting (MA) and the management accountant based on …

Background Vaccination is a cornerstone of the prevention of communicable infectious
diseases; however, vaccines have traditionally met with public fear and hesitancy, and …

Although generative adversarial networks (GANs) have made significant progress in face
synthesis, there lacks enough understanding of what GANs have learned in the latent …

In the post-COVID-19 era, the importance of green finance in green recovery is underlined.
As a financial instrument serving green development, green bonds promise to raise funds to …

We argue word embedding models are a useful tool for the study of culture using a historical
analysis of shared understandings of social class as an empirical case. Word embeddings …

The green credit policy is expected to be an effective financial instrument for achieving
energy conservation and emission reduction. This policy would discourage sectors of high …

In this work we propose a deep adaptive sampling (DAS-PINNs) method for solving partial
differential equations (PDEs), where deep neural networks are utilized to approximate the …

Whereas diverse variations of diffusion models exist, extending the linear diffusion into a
nonlinear diffusion process is investigated by very few works. The nonlinearity effect has …

This paper examines consciousness from the perspective of theoretical computer science
(TCS), a branch of mathematics concerned with understanding the underlying principles of …