Vincent Michalski

Computer Vision and Pattern Recognition · 2014–2018

A researcher in the Science corpus: 11 papers; trusts 416 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Vincent Michalski trusts overall

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

  1. Geoffrey E. Hinton
  2. Roland Memisevic
  3. Yoshua Bengio
  4. Ilya Sutskever
  5. Yann LeCun
  6. J. Urgen Schmidhuber
  7. Alex Krizhevsky
  8. Diederik P. Kingma
  9. Kaiming He
  10. Sepp Hochreiter

Who trusts Vincent Michalski overall

  1. Dinesh Jayaraman
  2. Kristen Grauman
  3. William Lotter
  4. Scott E. Reed
  5. Felix Leibfried
  6. Marc'Aurelio Ranzato
  7. Nitish Srivastava
  8. Honglak Lee
  9. Shan Li
  10. Abhinav Kumar Gupta

Papers from Vincent Michalski's perspective

Ordered by how strongly the researchers Vincent Michalski 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. Long Short-Term Memory
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers