Ahmed Elnaggar

According to our database, Ahmed Elnaggar authored at least 12 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Ankh: Optimized Protein Language Model Unlocks General-Purpose Modelling.

Ahmed Elnaggar, Hazem Essam, Wafaa Salah-Eldin, Walid Moustafa, Mohamed Elkerdawy, Charlotte Rochereau, Burkhard Rost

CoRR, 2023

A journey into the Generative AI and large language models: From NLP to BioInformatics.

Ahmed Elnaggar

Proceedings of the International Conference on Grammatical Inference, 2023

2022

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning.

Ahmed Elnaggar, Michael Heinzinger, Christian Dallago, Ghalia Rehawi, Yu Wang, Llion Jones, Tom Gibbs, Tamas Feher, Christoph Angerer, Martin Steinegger, Debsindhu Bhowmik, Burkhard Rost

IEEE Trans. Pattern Anal. Mach. Intell., 2022

2021

CodeTrans: Towards Cracking the Language of Silicone's Code Through Self-Supervised Deep Learning and High Performance Computing.

Ahmed Elnaggar, Wei Ding, Llion Jones, Tom Gibbs, Tamas Feher, Christoph Angerer, Silvia Severini, Florian Matthes, Burkhard Rost

CoRR, 2021

Automated Employee Objective Matching Using Pre-trained Word Embeddings.

Mohab Ghanem, Ahmed Elnaggar, Adam Mckinnon, Christian Debes, Olivier Boisard, Florian Matthes

Proceedings of the 25th IEEE International Enterprise Distributed Object Computing Conference, 2021

2020

ProtTrans: Towards Cracking the Language of Life's Code Through Self-Supervised Deep Learning and High Performance Computing.

Ahmed Elnaggar, Michael Heinzinger, Christian Dallago, Ghalia Rehawi, Yu Wang, Llion Jones, Tom Gibbs, Tamas Feher, Christoph Angerer, Martin Steinegger, Debsindhu Bhowmik, Burkhard Rost

CoRR, 2020

2019

Modeling aspects of the language of life through transfer-learning protein sequences.

Michael Heinzinger, Ahmed Elnaggar, Yu Wang, Christian Dallago, Dmitrii Nechaev, Florian Matthes, Burkhard Rost

BMC Bioinform., 2019

2018

Named-Entity Linking Using Deep Learning For Legal Documents: A Transfer Learning Approach.

Ahmed Elnaggar, Robin Otto, Florian Matthes

CoRR, 2018

A Machine Learning Based Approach to Application Landscape Documentation.

Jörg Landthaler, Ömer Uludag, Gloria Bondel, Ahmed Elnaggar, Saasha Nair, Florian Matthes

Proceedings of the Practice of Enterprise Modeling - 11th IFIP WG 8.1. Working Conference, PoEM 2018, Vienna, Austria, October 31, 2018

Stop Illegal Comments: A Multi-Task Deep Learning Approach.

Ahmed Elnaggar, Bernhard Waltl, Ingo Glaser, Jörg Landthaler, Elena Scepankova, Florian Matthes

Proceedings of the 2018 Artificial Intelligence and Cloud Computing Conference, 2018

Deep Learning for Named-Entity Linking with Transfer Learning for Legal Documents.

Ahmed Elnaggar, Robin Otto, Florian Matthes

Proceedings of the 2018 Artificial Intelligence and Cloud Computing Conference, 2018

Multi-Task Deep Learning for Legal Document Translation, Summarization and Multi-Label Classification.

Ahmed Elnaggar, Christoph Gebendorfer, Ingo Glaser, Florian Matthes

Proceedings of the 2018 Artificial Intelligence and Cloud Computing Conference, 2018