Nedjma Djouhra Ousidhoum
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 61 citations into it; #26,200 of 35,345 by trust here, #16,771 by citations
- Natural Language Processing — 47 citations into it; #4,294 of 5,688 by trust here, #3,421 by citations
Whom Nedjma Djouhra Ousidhoum trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Marco Tulio Ribeiro
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- Diederik P. Kingma
- Thomas Davidson
- Ronan Collobert
- Alex Krizhevsky
- Yann LeCun
- Richard Socher
Who trusts Nedjma Djouhra Ousidhoum overall
- Endang Wahyu Pamungkas
- Debora Nozza
- Bertie Vidgen
- Valerio Basile
- Binny Mathew
- Federico Bianchi
- Viviana Patti
- Waiman Si
- Leon Derczynski
- Sachin Kumar
Papers from Nedjma Djouhra Ousidhoum's perspective
Ordered by how strongly the researchers Nedjma Djouhra Ousidhoum trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- 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
- Multilingual and Multi-Aspect Hate Speech Analysis (2019) — 347 citations
- Probing Toxic Content in Large Pre-Trained Language Models (2021) — 148 citations