The key processes in biological and chemical systems are described by networks of
chemical reactions. From molecular biology to biotechnology applications, computational …

The phenomena of climate change and increase in warming conditions across the globe
causes changes in the frequency and severity of extreme weather events. The present study …

Democratization of machine learning requires architectures that automatically adapt to new
problems. Neural Differential Equations (NDEs) have emerged as a popular modeling …

In this paper, a novel parameter estimation method based on a two-stage neural network
(PENN) is proposed to carry out a joint estimation of a parameterized stochastic differential …

The variability in the extreme rainfall events is of growing concern in the context of climate
change. Several high rainfall events have occurred in India in recent years and simulations …

Bayesian and non-Bayesian moment-based inference methods are commonly used to
estimate the parameters defining stochastic models of gene regulatory networks from noisy …

This paper, using Ireland as a case study, examines the relationship between rural
economic activities and river water quality. The stipulation from the EU water framework …

Estimating uncertainty in model predictions is a central task in quantitative biology.
Biological models at the single-cell level are intrinsically stochastic and nonlinear, creating …

The democratization of machine learning requires architectures that automatically adapt to
new problems. Neural Differential Equations have emerged as a popular modeling …

This study aims to analyze the influence of GDP, population, distance, similarity index of
economic size, and exchange rate on Indonesian exports with ASEAN countries and 7 …