Adam Prügel-Bennett

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 5 papers; trusts 576 researchers and is trusted by 41 researchers here, as inferred from the citation graph.

Subfields

Whom Adam Prügel-Bennett trusts overall

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

  1. Geoffrey E. Hinton
  2. Alex Krizhevsky
  3. Yoshua Bengio
  4. Diederik P. Kingma
  5. Kaiming He
  6. Yann LeCun
  7. Ilya Sutskever
  8. Karen Simonyan
  9. Alex Graves
  10. Ross B. Girshick

Who trusts Adam Prügel-Bennett overall

  1. Yan Zhang
  2. David W. Zhang
  3. Adam R. Kosiorek
  4. Zhou Yu
  5. Carl Yang
  6. Qian Huang
  7. Marco Tulio Ribeiro
  8. Gertjan J. Burghouts
  9. Swarnadeep Saha
  10. Enas Elgeldawi

Papers from Adam Prügel-Bennett's perspective

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

Their papers