Emma Gowen

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Emma Gowen trusts overall

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

  1. Gaël Varoquaux
  2. M. Stone
  3. Sudhir Varma
  4. Etienne Combrisson
  5. Bernhard E. Boser
  6. Mohammad R. Arbabshirani

Papers from Emma Gowen's perspective

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

  1. A training algorithm for optimal margin classifiers
  2. Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls (NeuroImage)
  3. Assessing and tuning brain decoders: Cross‐validation, caveats, and guidelines (NeuroImage)
  4. Scikit-learn: Machine Learning in Python
  5. Exceeding chance level by chance: The caveat of theoretical chance levels in brain signal classification and statistical assessment of decoding accuracy. (Journal of Neuroscience Methods)
  6. Cross‐Validatory Choice and Assessment of Statistical Predictions
  7. Bias in error estimation when using cross-validation for model selection (BMC Bioinformatics)
  8. Optimal number of features as a function of sample size for various classification rules (Bioinform.)
  9. Machine learning in genetics and genomics (Nature reviews genetics)
  10. Cross-validation pitfalls when selecting and assessing regression and classification models (Journal of Cheminformatics)

Their papers