Paul Vicol

Artificial Intelligence · 2018–2025

A researcher in the Science corpus: 8 papers; trusts 356 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

Whom Paul Vicol trusts overall

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

  1. Alex Krizhevsky
  2. Geoffrey E. Hinton
  3. Diederik P. Kingma
  4. Yoshua Bengio
  5. Yann LeCun
  6. Ilya Sutskever
  7. Alex Graves
  8. J. Urgen Schmidhuber
  9. Kaiming He
  10. Radford M. Neal

Who trusts Paul Vicol overall

  1. Dustin Tran
  2. Xuanyi Dong
  3. Yaoyao Liu
  4. Yeming Wen
  5. Laurent Valentin Jospin
  6. Erik A. Daxberger
  7. Jonathan Lorraine
  8. Danijar Hafner
  9. Timothy Nguyen
  10. Zalán Borsos

Papers from Paul Vicol's perspective

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

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

Their papers