Pascal Kerschke

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Pascal Kerschke trusts overall

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

  1. Frank Hutter
  2. Kevin Leyton-Brown
  3. Lars Kotthoff
  4. Radford M. Neal
  5. Holger H. Hoos
  6. Jerome H. Friedman
  7. Vladimir Naumovich Vapni
  8. Thomas G. Dietterich
  9. David Ruppert
  10. Malte Helmert

Who trusts Pascal Kerschke overall

  1. Aman Madaan
  2. Philipp Probst

Papers from Pascal Kerschke's perspective

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

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

Their papers