Karl Pertsch

Artificial Intelligence · 2018–2025

A researcher in the Science corpus: 16 papers; trusts 423 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Karl Pertsch trusts overall

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

  1. Diederik P. Kingma
  2. Sergey Levine
  3. Geoffrey E. Hinton
  4. Chelsea Finn
  5. Alex Graves
  6. Richard S. Sutton
  7. Yoshua Bengio
  8. Ronald J. Williams
  9. Alex Krizhevsky
  10. Danilo Jimenez Rezende

Who trusts Karl Pertsch overall

  1. Moritz Reuss
  2. Taewook Nam
  3. Moo Jin Kim
  4. Tim Pearce
  5. Shao-Hua Sun
  6. Qingwen Bu
  7. Maximilian Xiling Li
  8. Yueen Ma

Papers from Karl Pertsch's perspective

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

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

Their papers