Nesreen K. Ahmed

Artificial Intelligence · 2010–2023

A researcher in the Science corpus: 6 papers; trusts 45 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 202 citations into it; #16,335 of 35,345 by trust here, #9,870 by citations
• Natural Language Processing — 89 citations into it
• Computer Vision and Pattern Recognition — 42 citations into it; #11,826 of 21,575 by trust here, #11,950 by citations
• Graph Learning — 42 citations into it
• Statistical and Nonlinear Physics — 39 citations into it; #3,017 of 10,127 by trust here, #2,437 by citations
• Representation & Self-Supervised Learning — 27 citations into it
• Molecular Biology — 24 citations into it; #6,934 of 17,773 by trust here, #14,176 by citations
• Statistics and Probability — 8 citations into it

Whom Nesreen K. Ahmed trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. David John Cameron MacKay
2. Christopher K. I. Williams
3. Eric R. Ziegel
4. W. Härdle
5. Ramesh Sharda
6. Spyros Makridakis
7. Geoffrey E. Hinton
8. Yoshua Bengio
9. Ilya Sutskever
10. Diederik P. Kingma

Who trusts Nesreen K. Ahmed overall

1. Weizhong Yan
2. Iis P. Tussyadiah
3. Spyros Makridakis
4. Bryan Lim
5. A. Navon
6. Robert Andrawis
7. Scott Alfeld
8. Jing Huang
9. Corey Snyder
10. Seyed Mehran Kazemi

Papers from Nesreen K. Ahmed's perspective

Ordered by how strongly the researchers Nesreen K. Ahmed trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Attention Models in Graphs (2018) — 175 citations
• Graph Neural Networks with Heterophily (2020) — 406 citations
• The Network Data Repository with Interactive Graph Analytics and Visualization (2015) — 3,002 citations
• Bias and Fairness in Large Language Models: A Survey (2023) — 1,188 citations
• Continuous-Time Dynamic Network Embeddings (2018) — 646 citations
• An Empirical Comparison of Machine Learning Models for Time Series Forecasting (2010) — 764 citations