Mohammed Saeed
Artificial Intelligence · with Ahmadi · 2019–2021
A researcher in the Science corpus: 2 papers; trusts 42 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 47 citations into it; #25,243 of 35,345 by trust here, #28,481 by citations
- Natural Language Processing — 30 citations into it; #4,183 of 5,688 by trust here, #4,983 by citations
- Computer Vision and Pattern Recognition — 14 citations into it
- Evaluation & Benchmarks — 8 citations into it
- Graph Learning — 7 citations into it
- Information Systems — 6 citations into it
- Knowledge Graphs & Representation — 5 citations into it; #170 of 226 by trust here, #201 by citations
Whom Mohammed Saeed trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Percy Liang
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Jason Aaron Edward Weston
- Ilya Sutskever
- Jacob Devlin
- Alex Krizhevsky
- Joohyung Lee
- Gianluca Demartini
Who trusts Mohammed Saeed overall
Papers from Mohammed Saeed's perspective
Ordered by how strongly the researchers Mohammed Saeed trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- RuleBERT: Teaching Soft Rules to Pre-Trained Language Models (2021) — 37 citations
- Explainable Fact Checking with Probabilistic Answer Set Programming (2019) — 59 citations