Aynaz Taheri

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 2 papers; trusts 175 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it; #23,971 of 35,345 by trust here, #19,018 by citations
• Graph Learning — 26 citations into it
• Natural Language Processing — 24 citations into it; #4,007 of 5,688 by trust here, #3,754 by citations
• Computer Vision and Pattern Recognition — 17 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Statistical and Nonlinear Physics — 6 citations into it
• Computational Theory and Mathematics — 5 citations into it
• Molecular Biology — 5 citations into it

Whom Aynaz Taheri trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Tomas Mikolov
3. Ilya Sutskever
4. Sepp Hochreiter
5. Quoc V. Le
6. Yoshua Bengio
7. Chih-Jen Lin
8. Oriol Vinyals
9. Alex Krizhevsky
10. J. Urgen Schmidhuber

Who trusts Aynaz Taheri overall

1. Kaixiong Zhou
2. Qingquan Song
3. D. Gunning
4. Xia Hu
5. Qiaoyu Tan
6. Xiao Huang
7. Joshua Feldman
8. Hongming Zhang
9. Peifeng Wang
10. Antoine Bosselut

Papers from Aynaz Taheri's perspective

Ordered by how strongly the researchers Aynaz Taheri trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Commonsense Knowledge Base Completion (2016) — 180 citations
• Learning Graph Representations with Recurrent Neural Network Autoencoders (2018) — 49 citations