Erran L. Li

Computer Networks and Communications · 2001–2019

A researcher in the Science corpus: 12 papers; trusts 30 researchers and is trusted by 33 researchers here, as inferred from the citation graph.

Subfields

Whom Erran L. Li trusts overall

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

  1. Wendi Rabiner Heinzelman
  2. Ram Ramanathan
  3. Roger Wattenhofer
  4. Anantha P. Chandrakasan
  5. Hari Balakrishnan
  6. Joseph Y. Halpern
  7. Rob Sherwood
  8. Jennifer Rexford
  9. Paramvir Victor Bahl
  10. Li Li

Who trusts Erran L. Li overall

  1. Di Tian
  2. Paolo Santi
  3. Kemal Akkaya
  4. Samina Ehsan
  5. Nicolas D. Georganas
  6. Rajmohan Rajaraman
  7. Adamu Murtala Zungeru
  8. Roger Wattenhofer
  9. Ritesh Madan
  10. Errol L. Lloyd

Papers from Erran L. Li's perspective

Ordered by how strongly the researchers Erran L. Li 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. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  3. ImageNet classification with deep convolutional neural networks
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Energy-efficient communication protocol for wireless microsensor networks (Proceedings of the Annual Hawaii International Conference on System Sciences)
  6. OpenFlow: enabling innovation in campus networks (CCRV)
  7. Topology control of multihop wireless networks using transmit power adjustment (Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064))
  8. Wireless integrated network sensors (Communications of the ACM)
  9. VL2: a scalable and flexible data center network (Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers