Eyal Amir

Probabilistic & Bayesian Methods · 2002–2011

A researcher in the Science corpus: 5 papers; trusts 14 researchers and is trusted by 93 researchers here, as inferred from the citation graph.

Subfields

Whom Eyal Amir trusts overall

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

  1. John McCarthy
  2. Andrew Barto
  3. Santosh Srinivas Vempala
  4. Drew V. McDermott
  5. Albert Tarantola
  6. Raymond Reiter
  7. Fahiem Bacchus
  8. David Poole
  9. Kevin P. Murphy
  10. Stuart J. Russell

Who trusts Eyal Amir overall

  1. Daniel S. Brown
  2. Scott Niekum
  3. Sergey Levine
  4. Manuel Lopes
  5. Kun Li
  6. Vaishak Belle
  7. Pieter Abbeel
  8. Yuchen Cui
  9. J. Bagnell
  10. Chelsea Finn

Papers from Eyal Amir's perspective

Ordered by how strongly the researchers Eyal Amir 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. Attention is All you Need (Neural Information Processing Systems)
  7. Learning Multiple Layers of Features from Tiny Images
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Reinforcement Learning: An Introduction
  10. ImageNet: A large-scale hierarchical image database

Their papers