Samuel B. Hopkins

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Samuel B. Hopkins trusts overall

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

  1. Thorsten Bernholt
  2. Daniel J. Hsu
  3. Tengyu Ma
  4. Boaz Barak
  5. Ilias Diakonikolas
  6. David Steurer
  7. Sham M. Kakade
  8. Sanjeev Arora
  9. Rocco A. Servedio
  10. Leslie G. Valiant

Who trusts Samuel B. Hopkins overall

  1. Yu Cheng
  2. Ilias Diakonikolas
  3. Pravesh Kothari
  4. Rong Ge
  5. Jerry Zheng Li
  6. Gautam Kamath
  7. Sanjeev Arora

Papers from Samuel B. Hopkins's perspective

Ordered by how strongly the researchers Samuel B. Hopkins 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. Attention is All you Need (Neural Information Processing Systems)
  6. Learning Multiple Layers of Features from Tiny Images
  7. Long Short-Term Memory
  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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers