Aaron Mishkin

Optimization & Training · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 55 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Aaron Mishkin trusts overall

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

  1. Alex Graves
  2. Geoffrey E. Hinton
  3. Diederik P. Kingma
  4. Yoshua Bengio
  5. Alex Krizhevsky
  6. Yann LeCun
  7. Shun-ichi Amari
  8. Radford M. Neal
  9. Ilya Sutskever
  10. Kaiming He

Who trusts Aaron Mishkin overall

  1. Frederik Kunstner
  2. Nicolas Loizou
  3. Philipp Hennig
  4. Leonard Berrada

Papers from Aaron Mishkin's perspective

Ordered by how strongly the researchers Aaron Mishkin 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. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Learning Multiple Layers of Features from Tiny Images
  7. Attention is All you Need (Neural Information Processing Systems)
  8. ImageNet: A large-scale hierarchical image database
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers