Shansan Gong

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Natural Language Processing — 22 citations into it
• Generative Models — 21 citations into it
• Evaluation & Benchmarks — 7 citations into it
• Probabilistic & Bayesian Methods — 5 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Shansan Gong trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Jonathan Ho
5. Alex Krizhevsky
6. Ilya Sutskever
7. Philipp Koehn
8. Alex Nichol
9. Yann LeCun
10. Kyunghyun Cho

Who trusts Shansan Gong overall

1. Zeqian Ju

Papers from Shansan Gong's perspective

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

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

Their papers

• DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models (2022) — 592 citations