3 code implementations • 6 Jun 2019 • Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
In exploration seismology, seismic inversion refers to the process of inferring physical properties of the subsurface from seismic data.
1 code implementation • 15 Dec 2022 • Ahmad Mustafa, Ghassan AlRegib
Deep learning can extract rich data representations if provided sufficient quantities of labeled training data.
no code implementations • WS 2019 • Ahmad Ragab, Haitham Seelawi, Mostafa Samir, Abdelrahman Mattar, Hesham Al-Bataineh, Mohammad Zaghloul, Ahmad Mustafa, Bashar Talafha, Abed Alhakim Freihat, Hussein Al-Natsheh
In this paper we discuss several models we used to classify 25 city-level Arabic dialects in addition to Modern Standard Arabic (MSA) as part of MADAR shared task (sub-task 1).
no code implementations • 19 Sep 2019 • Hesham Al-Bataineh, Wael Farhan, Ahmad Mustafa, Haitham Seelawi, Hussein T. Al-Natsheh
Question semantic similarity is a challenging and active research problem that is very useful in many NLP applications, such as detecting duplicate questions in community question answering platforms such as Quora.
no code implementations • 12 Sep 2019 • Haitham Seelawi, Ahmad Mustafa, Hesham Al-Bataineh, Wael Farhan, Hussein T. Al-Natsheh
Question semantic similarity (Q2Q) is a challenging task that is very useful in many NLP applications, such as detecting duplicate questions and question answering systems.
no code implementations • 28 Jun 2020 • Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
We empirically compare our proposed workflow with some other sequence modeling-based neural networks that model seismic data only temporally.
no code implementations • 23 Jun 2022 • Yash-yee Logan, Ryan Benkert, Ahmad Mustafa, Gukyeong Kwon, Ghassan AlRegib
For this purpose, we propose a framework that incorporates clinical insights into the sample selection process of active learning that can be incorporated with existing algorithms.
no code implementations • 15 Dec 2022 • Ahmad Mustafa, Ghassan AlRegib
On a dataset of well outcomes and corresponding geophysical attribute data, we show how LIME can induce trust in model's decisions by revealing the decision-making process to be aligned to domain knowledge.