Matthew Joseph

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 12 papers; trusts 101 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

Whom Matthew Joseph trusts overall

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

  1. Cynthia Dwork
  2. John C. Duchi
  3. Adam D. Smith
  4. Raef Bassily
  5. Ú. Erlingsson
  6. Moritz Hardt
  7. Aaron Roth
  8. Kobbi Nissim
  9. Jayadev Acharya
  10. Lihong Li

Who trusts Matthew Joseph overall

  1. Michael Kearns
  2. Aaron Roth
  3. Luca Oneto
  4. Shira Mitchell
  5. Cynthia Dwork
  6. Dana Pessach
  7. Yahav Bechavod
  8. Sorelle A. Friedler
  9. Swati Gupta
  10. Silvia Chiappa

Papers from Matthew Joseph's perspective

Ordered by how strongly the researchers Matthew Joseph 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. 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. 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