Jon Barker

Signal Processing · with Vincent · 2006–2020

A researcher in the Science corpus: 9 papers; trusts 24 researchers and is trusted by 71 researchers here, as inferred from the citation graph.

Subfields

Whom Jon Barker trusts overall

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

  1. Daniel Povey
  2. Xavier Anguera Miró
  3. Andreas Stolcke
  4. Emmanuel Vincent
  5. Angelo Farina
  6. Arnab Ghoshal
  7. Martin P. Cooke
  8. Chuck Wooters
  9. Seiya Tokui
  10. Karel Veselý

Who trusts Jon Barker overall

  1. Mirco Ravanelli
  2. Shinji Watanabe
  3. Zhong Meng
  4. Emmanuel Vincent
  5. Yoshua Bengio
  6. Jinyu Li
  7. Maurizio Omologo
  8. Zixing Zhang
  9. Philemon Brakel
  10. Jürgen T. Geiger

Papers from Jon Barker's perspective

Ordered by how strongly the researchers Jon Barker 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. Long Short-Term Memory
  4. ImageNet classification with deep convolutional neural networks
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  8. The Kaldi Speech Recognition Toolkit
  9. Recurrent neural network based language model
  10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers