Emily Mower Provost

Artificial Intelligence · 2007–2017

A researcher in the Science corpus: 7 papers; trusts 50 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

Whom Emily Mower Provost trusts overall

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

  1. Geoffrey E. Hinton
  2. Björn Schuller
  3. Yoshua Bengio
  4. Alex Krizhevsky
  5. Abdel-rahman Mohamed
  6. Honglak Lee
  7. Yann LeCun
  8. Radford M. Neal
  9. Ilya Sutskever
  10. Diederik P. Kingma

Who trusts Emily Mower Provost overall

  1. Carlos Busso
  2. Reza Lotfian
  3. Qi-rong Mao
  4. Björn Schuller
  5. Jinkyu Lee
  6. Soujanya Poria
  7. Kun Han
  8. Ivan J. Tashev
  9. Shrikanth S. Narayanan
  10. Zhengwei Huang

Papers from Emily Mower Provost's perspective

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