Wenhao Yu
Artificial Intelligence · with Turk · 2017–2023
A researcher in the Science corpus: 7 papers; trusts 314 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 393 citations into it; #15,756 of 35,345 by trust here, #9,275 by citations
- Natural Language Processing — 201 citations into it
- Computer Vision and Pattern Recognition — 146 citations into it
- Reinforcement Learning — 77 citations into it; #1,237 of 2,242 by trust here, #1,300 by citations
- Large Language Models — 62 citations into it
- Information Systems — 48 citations into it
- Control and Systems Engineering — 35 citations into it; #2,041 of 8,257 by trust here, #1,439 by citations
- Computational Theory and Mathematics — 26 citations into it
Whom Wenhao Yu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sergey Levine
- John Schulman
- Pieter Abbeel
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Richard S. Sutton
- Ilya Sutskever
- J. Urgen Schmidhuber
Who trusts Wenhao Yu overall
- Xue Bin Peng
- Jie Tan
- Lerrel Pinto
- Shaojun Zhu
- Julian Ibarz
- Sergey Levine
- Shagun Sodhani
- Agrim Gupta
- Pieter Abbeel
- Marcin Andrychowicz
Papers from Wenhao Yu's perspective
Ordered by how strongly the researchers Wenhao Yu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Preparing for the Unknown: Learning a Universal Policy with Online System Identification (2017) — 368 citations
- Language to Rewards for Robotic Skill Synthesis (2023) — 422 citations
- A Survey of Deep Learning for Mathematical Reasoning (2022) — 204 citations
- A Survey of Knowledge-enhanced Text Generation (2020) — 345 citations
- Learning Novel Policies For Tasks (2019) — 35 citations
- Learning symmetric and low-energy locomotion (2018) — 223 citations
- Knowledge-Augmented Methods for Natural Language Processing (2023) — 21 citations