Yongxu Zhu

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yongxu Zhu trusts overall

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

  1. Ding-Xuan Zhou
  2. Eugene Seneta
  3. Diederik P. Kingma
  4. Xavier Glorot

Papers from Yongxu Zhu's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Understanding the difficulty of training deep feedforward neural networks
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Multilayer feedforward networks are universal approximators
  6. Gradient-based learning applied to document recognition
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Long Short-Term Memory
  9. An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers