Chenhao Niu

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 36 citations into it
• Graph Learning — 18 citations into it
• Generative Models — 14 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it

Whom Chenhao Niu trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Max Welling
4. Yoshua Bengio
5. Alex Krizhevsky
6. Kaiming He
7. Yann LeCun
8. Keyulu Xu
9. Thomas Kipf
10. Ilya Sutskever

Who trusts Chenhao Niu overall

1. Hyungjin Chung
2. Arash Vahdat
3. Jaehyeong Jo
4. Clément Vignac
5. Ling Yang
6. Jong Chul Ye
7. Karsten Kreis
8. Seul Lee

Papers from Chenhao Niu's perspective

Ordered by how strongly the researchers Chenhao Niu 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Permutation Invariant Graph Generation via Score-Based Generative Modeling (2020) — 373 citations
• Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network (2019) — 1,893 citations