Megan Leszczynski

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 95 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Megan Leszczynski trusts overall

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

  1. Alex Krizhevsky
  2. Geoffrey E. Hinton
  3. Kaiming He
  4. Diederik P. Kingma
  5. Sergey Ioffe
  6. Yoshua Bengio
  7. Yann LeCun
  8. Ilya Sutskever
  9. L. Eon Bottou
  10. Christian Szegedy

Papers from Megan Leszczynski's perspective

Ordered by how strongly the researchers Megan Leszczynski 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. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  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