Dan Schmidt

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Dan Schmidt trusts overall

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

  1. Diederik P. Kingma
  2. Jia Deng
  3. Jimmy Ba
  4. Jun-Yan Zhu
  5. David R. Martin
  6. Geoffrey E. Hinton
  7. Kostadin Dabov
  8. Alex Krizhevsky

Papers from Dan Schmidt's perspective

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

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

Their papers