Michael Spranger

Artificial Intelligence · 2002–2022

A researcher in the Science corpus: 4 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Spranger trusts overall

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

  1. A.S. d'Avila Garcez
  2. Luciano Serafini
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Alex Krizhevsky
  6. Stephen H. Muggleton
  7. Son Dinh Tran
  8. Ross B. Girshick
  9. Ilya Sutskever
  10. Ivan Donadello

Papers from Michael Spranger's perspective

Ordered by how strongly the researchers Michael Spranger 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. 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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers