Richard J. Chappell

Artificial Intelligence · 2015

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 Richard J. Chappell trusts overall

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

  1. Yoshua Bengio

Papers from Richard J. Chappell's perspective

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

  1. Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
  2. Representation Learning: A Review and New Perspectives
  3. Multiple Classifier Systems
  4. ImageNet classification with deep convolutional neural networks
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Predictive Markers for AD in a Multi-Modality Framework: An Analysis of MCI Progression in the ADNI Population (NeuroImage)
  7. Automatic classification of MR scans in Alzheimer’s disease
  8. Gradient-based learning applied to document recognition
  9. Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment (NeuroImage)
  10. Rate of progression of mild cognitive impairment to dementia – meta‐analysis of 41 robust inception cohort studies (Acta Psychiatrica Scandinavica)

Their papers