Philipp Koch

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 4 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Philipp Koch trusts overall

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

  1. Diederik P. Kingma
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Jimmy Ba
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Sepp Hochreiter
  8. Ilya Sutskever
  9. M. McHugh
  10. Yann LeCun

Papers from Philipp Koch's perspective

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

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

Their papers