William J. Tastle

Artificial Intelligence · 2005–2013

A researcher in the Science corpus: 4 papers; trusts 24 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom William J. Tastle trusts overall

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

  1. Yoav Freund
  2. Robert A. Jacobs
  3. David E. Rumelhart
  4. Tin Kam Ho
  5. Robert E. Schapire
  6. Ludmila I. Kuncheva
  7. David Hilton Wolpert
  8. John J. Hopfield
  9. J. Ross Quinlan
  10. Geoffrey E. Hinton

Who trusts William J. Tastle overall

  1. Jerry J. Vaske
  2. J. Beaman
  3. Massimo Buscema
  4. Brenden M. Lake
  5. Humberto Barreto

Papers from William J. Tastle's perspective

Ordered by how strongly the researchers William J. Tastle 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Learning internal representations by error propagation
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers