Brian Patton

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 11 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Brian Patton trusts overall

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

  1. Diederik P. Kingma
  2. Jonathan Le Roux
  3. John R. Hershey
  4. Geoffrey E. Hinton
  5. Jimmy Ba
  6. Hakan Erdogan

Who trusts Brian Patton overall

  1. Scott Wisdom

Papers from Brian Patton's perspective

Ordered by how strongly the researchers Brian Patton trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. GENERATIVE ADVERSARIAL NETS
  5. Long Short-Term Memory
  6. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. Attention is All you Need (Neural Information Processing Systems)
  9. WaveNet: A Generative Model for Raw Audio
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers