Jun Zhang

Artificial Intelligence · with Petropulu · 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 Jun Zhang trusts

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

  1. Ding-Xuan Zhou (in Artificial Intelligence)
  2. Eugene Seneta (in Statistical and Nonlinear Physics)

Papers from Jun Zhang's perspective

Ordered by how strongly the researchers Jun Zhang 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. Multilayer feedforward networks are universal approximators
  4. An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel
  5. Solution of the multiuser downlink beamforming problem with individual SINR constraints (IEEE Transactions on Vehicular Technology)
  6. ImageNet classification with deep convolutional neural networks
  7. Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems (IEEE Wireless Communications Letters)
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Deep Learning Based Communication Over the Air
  10. Semidefinite Relaxation of Quadratic Optimization Problems (IEEE Signal Processing Magazine)

Their papers