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 ...
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 ...
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 ...
Integrating monitoring data to efficiently update reservoir pressure and CO2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse ...
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 ...
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