Virginia F. J. Newcombe

Computer Vision and Pattern Recognition · 2016–2022

A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Virginia F. J. Newcombe trusts overall

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

  1. Geoffrey E. Hinton
  2. Ilya Sutskever
  3. Alex Krizhevsky
  4. Yoshua Bengio
  5. Kaiming He
  6. Karen Simonyan
  7. Yann LeCun
  8. Sergey Ioffe
  9. Christian Szegedy
  10. Andrew Zisserman

Who trusts Virginia F. J. Newcombe overall

  1. Sergey I. Nikolenko
  2. Konstantinos Kamnitsas
  3. Guotai Wang
  4. Wenqi Li
  5. Qi-Yan Dou
  6. Jose Dolz
  7. Andriy Myronenko
  8. Fabian Isensee
  9. Ali Hatamizadeh
  10. Md. Zahangir Alom

Papers from Virginia F. J. Newcombe's perspective

Ordered by how strongly the researchers Virginia F. J. Newcombe trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Long Short-Term Memory
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet: A large-scale hierarchical image database
  10. GENERATIVE ADVERSARIAL NETS

Their papers