Justin R. Chumbley
Statistics and Probability · 2009–2012
A researcher in the Science corpus: 3 papers; trusts 16 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 17 citations into it
- Artificial Intelligence — 14 citations into it
- Cognitive Neuroscience — 7 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
- Probabilistic & Bayesian Methods — 5 citations into it
Whom Justin R. Chumbley trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoav Benjamini
- John Ashburner
- Thomas E. Nichols
- M. Pacifico
- Karl J. Friston
- Ruth Heller
- Christopher R. Genovese
- Satoru Hayasaka
- Chih-Jen Lin
- John K. Kruschke
Who trusts Justin R. Chumbley overall
- Craig M. Bennett
- Tijl Grootswagers
- Robert J. Adler
- Meng-Chuan Lai
- Michael B. Miller
- Susan G. Wardle
- Jonathan E. Taylor
- Srikanth Padmala
- George L. Wolford
- Simon B. Eickhoff
Papers from Justin R. Chumbley's perspective
Ordered by how strongly the researchers Justin R. Chumbley trusts endorse each paper. Same corpus, a different order for every researcher.
- Voxel-based morphometry--the methods.
- Bayes factors
- Statistical parametric maps in functional imaging: A general linear approach
- Pattern Recognition and Machine Learning
- Variational algorithms for approximate Bayesian inference
- False Discovery Control for Random Fields
- Comparing dynamic causal models (NeuroImage)
- False Discovery Rates for Spatial Signals
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Controlling the false discovery rate: a practical and powerful approach to multiple testing
Their papers
- False discovery rate revisited: FDR and topological inference using Gaussian random fields (2009) — 485 citations
- Topological FDR for neuroimaging (2010) — 476 citations
- Bayesian mixed-effects inference on classification performance in hierarchical data sets (2012) — 29 citations