Xiaoyang Wang
Artificial Intelligence · with Chen · 2011–2022
A researcher in the Science corpus: 4 papers; trusts 183 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 53 citations into it; #15,385 of 35,345 by trust here, #16,166 by citations
- Computer Vision and Pattern Recognition — 36 citations into it
- Natural Language Processing — 16 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
- Probabilistic & Bayesian Methods — 5 citations into it
Whom Xiaoyang Wang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Daniel Porath
- Pedro F. Felzenszwalb
- Ilya Sutskever
- Yoshua Bengio
- Alex Krizhevsky
- Ronald J. Williams
- Kevin P. Murphy
- Kaiming He
Who trusts Xiaoyang Wang overall
- Yanwei Fu
- Shichen Liu
- Tianyu Liu
- Ziming Zhang
- Timothy M. Hospedales
- Soravit Changpinyo
- Shafin Rahman
- Mingsheng Long
- Tao A. Xiang
- Jianmin Wang
Papers from Xiaoyang Wang's perspective
Ordered by how strongly the researchers Xiaoyang 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- AVSS 2011 demo session: A large-scale benchmark dataset for event recognition in surveillance video (2011) — 435 citations
- Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints (2020) — 90 citations
- A Unified Probabilistic Approach Modeling Relationships between Attributes and Objects (2013) — 79 citations
- Meta-learning without data via Wasserstein distributionally-robust model fusion (2022) — 24 citations