Shentong Mo

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Shentong Mo trusts

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

  1. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  2. Kaiming He (in Computer Vision and Pattern Recognition)
  3. Ross B. Girshick (in Computer Vision and Pattern Recognition)

Papers from Shentong Mo's perspective

Ordered by how strongly the researchers Shentong Mo trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  2. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Visualizing Data using t-SNE
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Gradient-based learning applied to document recognition
  8. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
  9. Context Encoders: Feature Learning by Inpainting
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers