Maximilian Baust

Artificial Intelligence · 2016–2023

A researcher in the Science corpus: 6 papers; trusts 54 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Maximilian Baust trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Sepp Hochreiter
  4. Diederik P. Kingma
  5. Alex Krizhevsky
  6. Yann LeCun
  7. J. Urgen Schmidhuber
  8. Yoshua Bengio
  9. Evan Shelhamer
  10. Ross B. Girshick

Papers from Maximilian Baust's perspective

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

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

Their papers