Reza Ghaeini
Artificial Intelligence · 2017–2019
A researcher in the Science corpus: 4 papers; trusts 43 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 52 citations into it; #18,087 of 35,345 by trust here, #15,542 by citations
- Natural Language Processing — 43 citations into it; #3,148 of 5,688 by trust here, #3,529 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
- Evaluation & Benchmarks — 7 citations into it
- Management Science and Operations Research — 7 citations into it
Whom Reza Ghaeini trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Richard Socher
- Ilya Sutskever
- Dzmitry Bahdanau
- Jimmy Ba
- Christopher D. Manning
- Yann LeCun
Who trusts Reza Ghaeini overall
- Piyawat Lertvittayakumjorn
- Sofia Serrano
- Pooya Moradi
- Xizhou Zhu
- Ryan Teehan
- Gagan Bansal
- Alon Jacovi
- Noah A. Smith
- Francesca Toni
- Nishant Kambhatla
Papers from Reza Ghaeini's perspective
Ordered by how strongly the researchers Reza Ghaeini trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference (2018) — 105 citations
- Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference (2018) — 99 citations
- A DEEP LEARNING APPROACH FOR CANCER DETECTION AND RELEVANT GENE IDENTIFICATION (2017) — 295 citations
- Entity-aware ELMo: Learning Contextual Entity Representation for Entity Disambiguation (2019) — 26 citations