Samuel G. Müller

Artificial Intelligence · 2021–2025

A researcher in the Science corpus: 4 papers; trusts 218 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Samuel G. Müller trusts overall

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

  1. Alex Krizhevsky
  2. Geoffrey E. Hinton
  3. Radford M. Neal
  4. Diederik P. Kingma
  5. Yoshua Bengio
  6. Yann LeCun
  7. Kaiming He
  8. Quoc V. Le
  9. Ilya Sutskever
  10. Barret Zoph

Who trusts Samuel G. Müller overall

  1. Noah Hollmann
  2. Shivam Garg
  3. Duncan C. McElfresh
  4. Hugo Touvron
  5. Dimitris Tsipras

Papers from Samuel G. Müller's perspective

Ordered by how strongly the researchers Samuel G. Müller 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers