Ian Vince McLoughlin

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ian Vince McLoughlin trusts overall

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

  1. Kaiming He
  2. Diederik P. Kingma
  3. Najim Dehak
  4. Geoffrey E. Hinton
  5. P. Loizou
  6. Sergey Ioffe
  7. Alex Krizhevsky
  8. Individualized Treat
  9. X. Zhang
  10. Alec Radford

Papers from Ian Vince McLoughlin's perspective

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

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

Their papers