Tomer D. Ullman

Artificial Intelligence · 2009–2023

A researcher in the Science corpus: 13 papers; trusts 368 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

Whom Tomer D. Ullman trusts overall

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

  1. Josh Tenenbaum
  2. Noah D. Goodman
  3. Geoffrey E. Hinton
  4. Susan Carey
  5. Drew V. McDermott
  6. Alison Gopnik
  7. Elizabeth S. Spelke
  8. György Gergely
  9. Chris L. Baker
  10. R. Baillargeon

Who trusts Tomer D. Ullman overall

  1. Josh Tenenbaum
  2. Nikolaus Kriegeskorte
  3. Noah D. Goodman
  4. Peter W. Battaglia
  5. Laura Schulz
  6. Kexin Yi
  7. Sjoerd van Steenkiste
  8. Jiajun Wu
  9. Michael Chang
  10. Tobias Gerstenberg

Papers from Tomer D. Ullman's perspective

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

Their papers