William V. Baxter

Computer Graphics and Computer-Aided Design · 2003–2006

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom William V. Baxter trusts overall

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

  1. Neil D. Lawrence
  2. Serge J. Belongie
  3. Keith Grochow
  4. Jitendra Malik
  5. Steven L. Martin
  6. Jens Harald Krüger
  7. David John Cameron MacKay
  8. Matthew A. Turk
  9. Ronald Fedkiw
  10. Jan Puzicha

Papers from William V. Baxter's perspective

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

Their papers