John D. Jakeman

Statistics and Probability · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom John D. Jakeman trusts overall

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

  1. Dongbin Xiu
  2. Ivan V. Oseledets
  3. Fabio Nobile
  4. Alireza Doostan
  5. Carl E. Rasmussen
  6. Heng Li
  7. Ivo Babuska
  8. Raúl Tempone
  9. G. Em Karniadakis
  10. Jan S. Hesthaven

Papers from John D. Jakeman's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations (SIAM Journal on Scientific Computing)
  3. A Stochastic Collocation Method for Elliptic Partial Differential Equations with Random Input Data (SIAM Review)
  4. High-Order Collocation Methods for Differential Equations with Random Inputs (SIAM Journal on Scientific Computing)
  5. A Taxonomy of Global Optimization Methods Based on Response Surfaces
  6. Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
  7. Global sensitivity analysis using polynomial chaos expansions (Reliability Engineering & System Safety)
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Inverse problems: A Bayesian perspective (Acta Numerica)
  10. Probabilistic collocation method for flow in porous media: Comparisons with other stochastic methods

Their papers