Lawrence H. Schwartz

Artificial Intelligence · 2003–2019

A researcher in the Science corpus: 12 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Lawrence H. Schwartz trusts

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

  1. Diederik P. Kingma (in Artificial Intelligence)
  2. Max Welling (in Artificial Intelligence)

Papers from Lawrence H. Schwartz's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
  3. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
  4. Support-Vector Networks
  5. Random Forests
  6. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
  7. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository (Journal of digital imaging)
  8. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). (European Journal of Cancer)
  9. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach (Nature Communications)
  10. Radiomics: Extracting more information from medical images using advanced feature analysis (European Journal of Cancer)

Their papers