Jason Jianjun Gu

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jason Jianjun Gu trusts

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

  1. Sam T. Roweis (in Computer Vision and Pattern Recognition)
  2. Lawrence K. Saul (in Computer Vision and Pattern Recognition)

Papers from Jason Jianjun Gu's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. A Fast Learning Algorithm for Deep Belief Nets
  3. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
  4. Extracting and composing robust features with denoising autoencoders
  5. Building high-level features using large scale unsupervised learning
  6. Nonlinear dimensionality reduction by locally linear embedding.
  7. Acoustic Modeling Using Deep Belief Networks
  8. Unsupervised feature learning for audio classification using convolutional deep belief networks
  9. Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition
  10. RADAR: an in-building RF-based user location and tracking system (Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064))

Their papers