Michel Lang

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 7 papers; trusts 12 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Michel Lang trusts overall

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

  1. Frank Hutter
  2. Bernd Bischl
  3. Mark A. Hall
  4. James Bergstra
  5. Diederik P. Kingma
  6. Jasper Snoek
  7. Geoffrey E. Hinton
  8. Yoshua Bengio
  9. Max Kuhn
  10. Alex Krizhevsky

Who trusts Michel Lang overall

  1. Philipp Probst
  2. Giuseppe Casalicchio
  3. Bernd Bischl
  4. Anne-Laure Boulesteix
  5. Przemyslaw Biecek
  6. Marc-André Zöller
  7. Christoph Molnar
  8. R. Couronné
  9. Pascal Kerschke
  10. Jakob Bossek

Papers from Michel Lang's perspective

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

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

Their papers