Paul-Christian Burkner

Statistics and Probability · 2017–2020

A researcher in the Science corpus: 6 papers; trusts 87 researchers and is trusted by 59 researchers here, as inferred from the citation graph.

Subfields

Whom Paul-Christian Burkner trusts overall

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

  1. Radford M. Neal
  2. Andrew Gelman
  3. Michael Betancourt
  4. John K. Kruschke
  5. Joseph Hilbe
  6. Matthew D. Hoffman
  7. Simon N. Wood
  8. J. Hadfield
  9. Yves Rosseel
  10. Carlos M. Carvalho

Who trusts Paul-Christian Burkner overall

  1. Michael Scharkow
  2. Gerhard E. Tutz
  3. Aitor Egurtzegi
  4. R. van de Schoot
  5. Lotte Meteyard
  6. Dominique Makowski
  7. Eric J. Pedersen
  8. David Meng-Chuen Chen
  9. Jakob-Moritz Eberl
  10. Nienke E. R. van Bueren

Papers from Paul-Christian Burkner's perspective

Ordered by how strongly the researchers Paul-Christian Burkner trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Sampling-Based Approaches to Calculating Marginal Densities
  2. Regression Shrinkage and Selection via the Lasso
  3. Monte Carlo Sampling Methods Using Markov Chains and Their Applications
  4. ImageNet classification with deep convolutional neural networks
  5. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. Estimating the Dimension of a Model
  8. Inference from Iterative Simulation Using Multiple Sequences
  9. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers