12 citations · 13 across the 7 of their papers we have counts for
7 papers
Grievance Politics vs. Policy Debates: A Cross-Platform Analysis of Conservative Discourse on Truth Social and Reddit
Yining Wang, Alhasan Abdellatif, Artemis Deligianni +3
We present the first large-scale comparative analysis of Truth Social and the most popular conservative Reddit communities, r/Conservative, r/conservatives, and r/Republican. Using…
Feature-Modulated UFNO for Improved Prediction of Multiphase Flow in Porous Media
Alhasan Abdellatif, Hannah P. Menke, Florian Doster +2
The UNet-enhanced Fourier Neural Operator (UFNO) extends the Fourier Neural Operator (FNO) by incorporating a parallel UNet pathway, enabling the retention of both high- and low-fr…
A Benchmark Dataset for Machine Learning Surrogates of Pore-Scale CO2-Water Interaction
Alhasan Abdellatif, Hannah P. Menke, Julien Maes +2
Accurately capturing the complex interaction between CO2 and water in porous media at the pore scale is essential for various geoscience applications, including carbon capture and…
A Deep-Learning Iterative Stacked Approach for Prediction of Reactive Dissolution in Porous Media
Marcos Cirne, Hannah Menke, Alhasan Abdellatif +3
Simulating reactive dissolution of solid minerals in porous media has many subsurface applications, including carbon capture and storage (CCS), geothermal systems and oil & gas rec…
Local Padding in Patch-Based GANs for Seamless Infinite-Sized Texture Synthesis
Alhasan Abdellatif, Ahmed H. Elsheikh, Hannah P. Menke
Texture models based on Generative Adversarial Networks (GANs) use zero-padding to implicitly encode positional information of the image features. However, when extending the spati…
Generation of non-stationary stochastic fields using Generative Adversarial Networks
Alhasan Abdellatif, Ahmed H. Elsheikh, Daniel Busby +1
In the context of generating geological facies conditioned on observed data, samples corresponding to all possible conditions are not generally available in the training set and he…
Generating unrepresented proportions of geological facies using Generative Adversarial Networks
Alhasan Abdellatif, Ahmed H. Elsheikh, Gavin Graham +2
In this work, we investigate the capacity of Generative Adversarial Networks (GANs) in interpolating and extrapolating facies proportions in a geological dataset. The new generated…