Anbang Ye

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Natural Language Processing — 16 citations into it

Whom Anbang Ye trusts

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

1. Melissa Roemmele (in Natural Language Processing)
2. Mark O. Riedl (in Artificial Intelligence)

Papers from Anbang Ye's perspective

Ordered by how strongly the researchers Anbang Ye 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. Language Models are Unsupervised Multitask Learners
3. Language Models are Few-Shot Learners (Neural Information Processing Systems)
4. Proximal Policy Optimization Algorithms (arXiv.org)
5. ImageNet classification with deep convolutional neural networks
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Gradient-based learning applied to document recognition
10. ImageNet: A large-scale hierarchical image database

Their papers

• Robust Preference Learning for Storytelling via Contrastive Reinforcement Learning (2022) — 15 citations