Ranit Aharonov
Artificial Intelligence · 2003–2020
A researcher in the Science corpus: 5 papers; trusts 8 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 41 citations into it
- Cellular and Molecular Neuroscience — 11 citations into it; #1,135 of 2,998 by trust here, #1,454 by citations
- Cognitive Neuroscience — 11 citations into it; #4,583 of 10,852 by trust here, #4,260 by citations
- Electrical and Electronic Engineering — 10 citations into it; #6,033 of 16,539 by trust here, #7,175 by citations
- Neuroscience — 6 citations into it
Whom Ranit Aharonov trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard Kempter
- Guoqiang Bi
- Wulfram Gerstner
- Sen Song
- Yoshua Bengio
- Jonathan E. Rubin
- Dzmitry Bahdanau
- Geoffrey E. Hinton
- Kenneth D. Miller
- Sarah Wiegreffe
Who trusts Ranit Aharonov overall
- Matthieu Gilson
- Pierre Yger
- Yotam Luz
- Nicolas Frémaux
- Razvan V. Florian
- Sami El Boustani
- Andreas Knoblauch
Papers from Ranit Aharonov's perspective
Ordered by how strongly the researchers Ranit Aharonov trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- A Survey of the State of Explainable AI for Natural Language Processing (2020) — 470 citations
- Identification of hundreds of conserved and nonconserved human microRNAs (2005) — 1,941 citations
- Learning Input Correlations through Nonlinear Temporally Asymmetric Hebbian Plasticity (2003) — 424 citations
- MicroRNAs accurately identify cancer tissue origin (2008) — 1,016 citations
- Corpus Wide Argument Mining - a Working Solution (2019) — 70 citations