Matthew L. Daggitt

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Matthew L. Daggitt trusts overall

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

  1. Xiaowei Huang
  2. Diederik P. Kingma
  3. Ian J. Goodfellow
  4. Shixiang Shane Gu
  5. Timon Gehr
  6. Christian Szegedy
  7. Jimmy Ba
  8. Han Xiao
  9. Geoffrey E. Hinton

Papers from Matthew L. Daggitt's perspective

Ordered by how strongly the researchers Matthew L. Daggitt trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Gradient-based learning applied to document recognition
  5. Intriguing properties of neural networks
  6. Learning Multiple Layers of Features from Tiny Images
  7. Long Short-Term Memory
  8. Explaining and Harnessing Adversarial Examples
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet: A large-scale hierarchical image database

Their papers