Mengyu Wang
Artificial Intelligence · 2020–2022
A researcher in the Science corpus: 3 papers; trusts 251 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 145 citations into it; #27,247 of 35,345 by trust here, #25,809 by citations
- Computer Vision and Pattern Recognition — 85 citations into it; #16,765 of 21,575 by trust here, #16,787 by citations
- Meta & Continual Learning — 36 citations into it; #848 of 1,041 by trust here, #897 by citations
- Representation & Self-Supervised Learning — 36 citations into it
- Computer Networks and Communications — 15 citations into it
- Safety, Robustness & Interpretability — 14 citations into it
- Model Architectures — 11 citations into it
- Epidemiology — 9 citations into it
Whom Mengyu Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Diederik P. Kingma
- Yann LeCun
- Yoshua Bengio
- Ilya Sutskever
- Ross B. Girshick
- Jimmy Ba
- X. Zhang
Who trusts Mengyu Wang overall
Papers from Mengyu Wang's perspective
Ordered by how strongly the researchers Mengyu Wang 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)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- CMG: A Class-Mixed Generation Approach to Out-of-Distribution Detection (2022) — 15 citations
- Continual Learning by Using Information of Each Class Holistically (2021) — 66 citations
- HRN: A Holistic Approach to One Class Learning (2020) — 71 citations