Asma Ben Abacha
Artificial Intelligence · 2010–2019
A researcher in the Science corpus: 4 papers; trusts 30 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 42 citations into it; #19,930 of 35,345 by trust here, #16,166 by citations
- Computer Vision and Pattern Recognition — 28 citations into it; #17,613 of 21,575 by trust here, #13,815 by citations
- Natural Language Processing — 25 citations into it
- Evaluation & Benchmarks — 10 citations into it
Whom Asma Ben Abacha trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Samuel R. Bowman
- Ido Dagan
- Pranav Rajpurkar
- Geoffrey E. Hinton
- Kaiming He
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Karen Simonyan
- Ilya Sutskever
Who trusts Asma Ben Abacha overall
- Petros Stavropoulos
- Di Jin
- Maryam Rahnemoonfar
- Dimitris Pappas
- Eileen Pan
- Xuehai He
- Sedigheh Eslami
- Juliano Rabelo
- Xiaoman Zhang
- Ion Androutsopoulos
Papers from Asma Ben Abacha's perspective
Ordered by how strongly the researchers Asma Ben Abacha trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- A dataset of clinically generated visual questions and answers about radiology images (2018) — 841 citations
- A question-entailment approach to question answering (2019) — 305 citations
- VQA-Med: Overview of the Medical Visual Question Answering Task at ImageCLEF 2019 (2019) — 322 citations
- CARAMBA: Concept, Assertion, and Relation Annotation using Machine-learning Based Approaches (2010) — 39 citations