Sean Talts

Statistics and Probability · 2018

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Sean Talts trusts overall

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

  1. Håvard Rue
  2. Michael Betancourt
  3. Thomas M. Hamill
  4. Daniel P. Simpson
  5. Omiros Papaspiliopoulos
  6. Tilmann Gneiting
  7. Geir-Arne Fuglstad
  8. Andrew Gelman
  9. Alp Kucukelbir
  10. Sara Martino

Who trusts Sean Talts overall

  1. Joeri Hermans
  2. Alexander A. Alemi
  3. George Papamakarios
  4. Andrew Gelman
  5. Ian S. Fischer
  6. Volodimir Begy
  7. Gilles Louppe
  8. David C. Sterratt

Papers from Sean Talts's perspective

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

  1. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
  2. Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
  3. Constructing Priors that Penalize the Complexity of Gaussian Random Fields (Journal of the American Statistical Association)
  4. Bayesian Computing with INLA: A Review
  5. Interpretation of Rank Histograms for Verifying Ensemble Forecasts
  6. Automatic Differentiation Variational Inference
  7. A General Framework for the Parametrization of Hierarchical Models
  8. The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo
  9. A Conceptual Introduction to Hamiltonian Monte Carlo
  10. Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds

Their papers