Yikang Shen

Artificial Intelligence · with Kim · 2023–2024

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 75 citations into it
• Model Architectures — 52 citations into it
• Computer Vision and Pattern Recognition — 40 citations into it
• Natural Language Processing — 15 citations into it
• Efficiency & Compression — 12 citations into it
• Hardware and Architecture — 10 citations into it
• Electrical and Electronic Engineering — 6 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Yikang Shen trusts overall

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

1. Tri Dao
2. Geoffrey E. Hinton
3. Noam Shazeer
4. Yoshua Bengio
5. J. Urgen Schmidhuber
6. Diederik P. Kingma
7. Alex Krizhevsky
8. Sepp Hochreiter
9. Ilya Sutskever
10. Yann LeCun

Papers from Yikang Shen's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Gated Linear Attention Transformers with Hardware-Efficient Training (2023) — 480 citations
• Parallelizing Linear Transformers with the Delta Rule over Sequence Length (2024) — 322 citations