Statistical models based on Gaussian random variables occupy a central position in modern data analysis, offering a mathematically tractable framework for inference, prediction and dimensionality ...

While the high-dimensional biological data have provided unprecedented data resources for the identification of biomarkers, consensus is still lacking on how to best analyze them. The recently ...

Abstract: Soft sensing technology plays a crucial role in the real-time monitoring and optimization of key industrial variables. Recently, Transformers have emerged as a promising tool for soft sensor ...

description [ICLR 2026][Causal Inference][Counterfactual explanations] This paper proposes L-GMVAE (Label-Conditional Gaussian Mixture VAE) and the LAPACE algorithm. By learning multiple Gaussian ...

CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...

In this tutorial, we demonstrate using Catalyst how to define chemical systems involving reactions which products are geometrically distributed random variables. As an example, we consider an ...