Adam N. Sanborn

Artificial Intelligence · 1999–2013

A researcher in the Science corpus: 6 papers; trusts 19 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Adam N. Sanborn trusts overall

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

  1. Radford M. Neal
  2. Roger N. Shepard
  3. T. Griffiths
  4. David John Cameron MacKay
  5. Thomas S. Ferguson
  6. Jessica B. Hamrick
  7. Simon J. Sheather
  8. Josh Tenenbaum
  9. Wilson S. Geisler
  10. Stuart Geman

Who trusts Adam N. Sanborn overall

  1. T. Griffiths
  2. Tomer D. Ullman
  3. Samuel J. Gershman
  4. Noah D. Goodman
  5. Josh Tenenbaum
  6. Falk Lieder
  7. Omri Abend
  8. Tobias Gerstenberg
  9. E. Vul
  10. Peter W. Battaglia

Papers from Adam N. Sanborn's perspective

Ordered by how strongly the researchers Adam N. Sanborn 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. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Going deeper with convolutions

Their papers