Afra Alishahi
Artificial Intelligence · 2010–2020
A researcher in the Science corpus: 6 papers; trusts 516 researchers and is trusted by 55 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 87 citations into it; #4,298 of 35,345 by trust here, #8,439 by citations
- Computer Vision and Pattern Recognition — 53 citations into it; #4,097 of 21,575 by trust here, #6,206 by citations
- Natural Language Processing — 50 citations into it; #1,017 of 5,688 by trust here, #1,801 by citations
- Model Architectures — 24 citations into it
- Multimodal Learning — 22 citations into it; #265 of 1,211 by trust here, #770 by citations
- Representation & Self-Supervised Learning — 21 citations into it; #963 of 3,145 by trust here, #1,692 by citations
- Speech & Audio — 13 citations into it; #252 of 1,076 by trust here, #452 by citations
- Signal Processing — 12 citations into it; #879 of 7,572 by trust here, #1,538 by citations
Whom Afra Alishahi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Grzegorz Chrupała
- Karen Simonyan
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Kaiming He
- Ilya Sutskever
- Andrew Zisserman
- Yann LeCun
Who trusts Afra Alishahi overall
- Yonatan Belinkov
- Grzegorz Chrupała
- William N. Havard
- David F. Harwath
- James R. Glass
- Herman Kamper
- Wei-Ning Hsu
- Jean-Pierre Chevrot
- Fahim Dalvi
- Bertrand Higy
Papers from Afra Alishahi's perspective
Ordered by how strongly the researchers Afra Alishahi 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Representation of Linguistic Form and Function in Recurrent Neural Networks (2016) — 164 citations
- Representations of language in a model of visually grounded speech signal (2017) — 135 citations
- Correlating Neural and Symbolic Representations of Language (2019) — 75 citations
- Encoding of phonology in a recurrent neural model of grounded speech (2017) — 60 citations
- Analyzing analytical methods: The case of phonology in neural models of spoken language (2020) — 27 citations
- A Probabilistic Computational Model of Cross-Situational Word Learning (2010) — 192 citations