Noah Hollmann

Artificial Intelligence · 2021–2025

A researcher in the Science corpus: 3 papers; trusts 66 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Noah Hollmann trusts overall

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

  1. Radford M. Neal
  2. Geoffrey E. Hinton
  3. Diederik P. Kingma
  4. Yoshua Bengio
  5. J. Urgen Schmidhuber
  6. Alex Krizhevsky
  7. Yann LeCun
  8. Ilya Loshchilov
  9. Jerome H. Friedman
  10. Jimmy Ba

Who trusts Noah Hollmann overall

  1. Stefan Hegselmann
  2. Samuel G. Müller
  3. Shivam Garg

Papers from Noah Hollmann's perspective

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

Their papers