Abstract: In contrast to the existing approaches that use discrete Conditional Random Field (CRF) models, we propose to use a Gaussian CRF model for the task of semantic segmentation. We propose a ...
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 ...
The repository contains R code used to model data inline with the methods presented in the preprint “Conditional Extremes With Graphical Models” [1]. Additionally, output (figures and tables) has been ...
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 ...
CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...
Integrating monitoring data to efficiently update reservoir pressure and CO2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse ...
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