Gábor Braun

Optimization & Training · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Gábor Braun trusts overall

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

  1. Martin Jaggi
  2. Dan Garber
  3. Elad Hazan
  4. Simon Lacoste-Julien
  5. Thorsten Joachims
  6. Thomas Kerdreux
  7. Boris Polyak
  8. Anton Osokin
  9. Philip Wolfe
  10. Ofer Meshi

Who trusts Gábor Braun overall

  1. Sebastian Pokutta
  2. Alejandro Carderera
  3. Thomas Kerdreux
  4. Cyrille W. Combettes
  5. Francesco Rinaldi
  6. David H. Gutman
  7. Fabian Pedregosa
  8. Javier F. Peña
  9. Hassan Mortagy
  10. Lewis Liu

Papers from Gábor Braun's perspective

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

Their papers