Jonathan Passerat-Palmbach

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 5 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jonathan Passerat-Palmbach trusts overall

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

  1. Kaiming He
  2. Alex Krizhevsky
  3. Geoffrey E. Hinton
  4. Yann LeCun
  5. Yoshua Bengio
  6. Jia Deng
  7. Ilya Sutskever
  8. Diederik P. Kingma
  9. Ross B. Girshick
  10. Yuri Boykov

Papers from Jonathan Passerat-Palmbach's perspective

Ordered by how strongly the researchers Jonathan Passerat-Palmbach 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. ImageNet: A large-scale hierarchical image database
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Learning Multiple Layers of Features from Tiny Images
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Going deeper with convolutions

Their papers