Andrius Vabalas
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
- Artificial Intelligence — 7 citations into it
- Molecular Biology — 7 citations into it
Whom Andrius Vabalas trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Gaël Varoquaux
- M. Stone
- Sudhir Varma
- Etienne Combrisson
- Bernhard E. Boser
- Mohammad R. Arbabshirani
- O. Devos
- Richard M. Simon
- K. Jerbi
- Fabian Pedregosa
Who trusts Andrius Vabalas overall
Papers from Andrius Vabalas's perspective
Ordered by how strongly the researchers Andrius Vabalas trusts endorse each paper. Same corpus, a different order for every researcher.
- A training algorithm for optimal margin classifiers
- Single Subject Prediction of Brain Disorders in Neuroimaging: Promises and Pitfalls (NeuroImage)
- Scikit-learn: Machine Learning in Python
- Assessing and tuning brain decoders: Cross‐validation, caveats, and guidelines (NeuroImage)
- 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)
- Cross‐Validatory Choice and Assessment of Statistical Predictions
- Bias in error estimation when using cross-validation for model selection (BMC Bioinformatics)
- Machine learning in genetics and genomics (Nature reviews genetics)
- Optimal number of features as a function of sample size for various classification rules (Bioinform.)
- Cross-validation pitfalls when selecting and assessing regression and classification models (Journal of Cheminformatics)
Their papers
- Machine learning algorithm validation with a limited sample size (2019) — 1,474 citations