David J. Nott

Statistics and Probability · with Drovandi · 2017

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom David J. Nott trusts overall

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

  1. MARK A. Beaumont
  2. Christophe Andrieu
  3. Radford M. Neal
  4. Simon N. Wood
  5. David I. Warton

Papers from David J. Nott's perspective

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

  1. The pseudo-marginal approach for efficient Monte Carlo computations
  2. Estimation of population growth or decline in genetically monitored populations.
  3. Statistical inference for noisy nonlinear ecological dynamic systems
  4. Approximate Bayesian computation in population genetics.
  5. Approximate Bayesian computational methods (Statistics and computing)
  6. Particle Markov chain Monte Carlo methods
  7. Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
  8. Handbook of Markov Chain Monte Carlo
  9. A well-conditioned estimator for large-dimensional covariance matrices
  10. Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows

Their papers