Muning Wen

Artificial Intelligence · 2022–2023

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 54 citations into it
• Reinforcement Learning — 27 citations into it

Whom Muning Wen trusts overall

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

1. Richard S. Sutton
2. Geoffrey E. Hinton
3. Kaiming He
4. Andrew Barto
5. Diederik P. Kingma
6. Tabish Rashid
7. Alex Krizhevsky
8. Yoshua Bengio
9. Christian Schröder de Witt
10. Jakob N. Foerster

Papers from Muning Wen's perspective

Ordered by how strongly the researchers Muning Wen 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. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training (2023) — 351 citations
• Multi-Agent Reinforcement Learning is a Sequence Modeling Problem (2022) — 362 citations