David Hoeller

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 4 papers; trusts 17 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom David Hoeller trusts overall

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

  1. John Schulman
  2. Jemin Hwangbo
  3. Sertac Karaman
  4. Viktor Makoviychuk
  5. E. Todorov
  6. N. Rudin
  7. Péter Fankhauser
  8. Pieter Abbeel
  9. Marco Hutter
  10. Sergey Levine

Who trusts David Hoeller overall

  1. Gabriel B. Margolis
  2. Tete Xiao
  3. Ananye Agarwal
  4. Ilija Radosavovic

Papers from David Hoeller's perspective

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

Their papers