Navid Naderializadeh

Electrical and Electronic Engineering · 2019

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Navid Naderializadeh trusts

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

  1. Kaiming He (in Model Architectures)
  2. Geoffrey Y. Li (in Artificial Intelligence)
  3. Shi Jin (in Electrical and Electronic Engineering)
  4. Chao-Kai Wen (in Electrical and Electronic Engineering)
  5. Karen Simonyan (in Computer Vision and Pattern Recognition)
  6. Andrew Zisserman (in Computer Vision and Pattern Recognition)

Papers from Navid Naderializadeh's perspective

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

  1. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  2. Deep Learning-Based Channel Estimation for Beamspace mmWave Massive MIMO Systems (IEEE Wireless Communications Letters)
  3. Deep Learning for Massive MIMO CSI Feedback (IEEE Wireless Communications Letters)
  4. Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems (IEEE Wireless Communications Letters)
  5. Model-Driven Deep Learning for Physical Layer Communications (IEEE wireless communications)
  6. Downlink Training Techniques for FDD Massive MIMO Systems: Open-Loop and Closed-Loop Training With Memory (IEEE Journal on Selected Topics in Signal Processing)
  7. Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems (IEEE Journal on Selected Topics in Signal Processing)
  8. An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems (IEEE Journal on Selected Topics in Signal Processing)
  9. Deep Learning in Physical Layer Communications (IEEE wireless communications)
  10. Convolutional neural networks at constrained time cost

Their papers