John Healy

Representation & Self-Supervised Learning · with McInnes · 2017–2018

A researcher in the Science corpus: 6 papers; trusts 72 researchers and is trusted by 180 researchers here, as inferred from the citation graph.

Subfields

Whom John Healy trusts overall

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

  1. Gunnar E. Carlsson
  2. L. V. D. van der Maaten
  3. Ricardo José Gabrielli Barreto Campello
  4. Mikhail Belkin
  5. Leland McInnes
  6. Geoffrey E. Hinton
  7. Joseph B. Kruskal
  8. Larry A. Wasserman
  9. Daniel Müllner
  10. Moo K. Chung

Who trusts John Healy overall

  1. Mohammad Rostami
  2. Maarten Grootendorst
  3. D. Angelov
  4. Pavlin Gregor Policar
  5. Dmitry Kobak
  6. Leland McInnes
  7. Edwin S. Dalmaijer
  8. Carlos Escolano
  9. Christoph Hafemeister
  10. Tim Sainburg

Papers from John Healy's perspective

Ordered by how strongly the researchers John Healy 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. Long Short-Term Memory
  6. Learning Multiple Layers of Features from Tiny Images
  7. Attention is All you Need (Neural Information Processing Systems)
  8. ImageNet: A large-scale hierarchical image database
  9. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers