Deanna Needell

Computational Mechanics · 2007–2016

A researcher in the Science corpus: 9 papers; trusts 80 researchers and is trusted by 254 researchers here, as inferred from the citation graph.

Subfields

Whom Deanna Needell trusts overall

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

  1. Thomas Strohmer
  2. E.J. Candes
  3. Joel A. Tropp
  4. Roman Vershynin
  5. Charles L. Byrne
  6. David L. Donoho
  7. Yurii E. Nesterov
  8. Francis R. Bach
  9. L. Eon Bottou
  10. Peter Richtárik

Who trusts Deanna Needell overall

  1. Nicolas Loizou
  2. Peter Richtárik
  3. Jakub Konecný
  4. Joel A. Tropp
  5. Mark A. Davenport
  6. Robert Mansel Gower
  7. Martin Takác
  8. Thomas Blumensath
  9. Francis R. Bach
  10. Arian Maleki

Papers from Deanna Needell's perspective

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

Their papers