T. Sullivan

Artificial Intelligence · with Cockayne · 2015–2017

A researcher in the Science corpus: 3 papers; trusts 22 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it; #20,036 of 35,345 by trust here, #25,809 by citations
• Statistics and Probability — 25 citations into it; #4,842 of 12,932 by trust here, #5,857 by citations
• Probabilistic & Bayesian Methods — 18 citations into it
• Statistical and Nonlinear Physics — 11 citations into it
• Numerical Analysis — 9 citations into it
• Numerical Methods & Scientific Computing — 7 citations into it
• Management Science and Operations Research — 6 citations into it

Whom T. Sullivan trusts overall

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

1. Andrew M. Stuart
2. Philipp Hennig
3. Masoumeh Dashti
4. Pierre Del Moral
5. David John Cameron MacKay
6. Andrew Gelman
7. James O. Berger
8. Persi Diaconis
9. Glenn Shafer
10. 採編典藏組

Who trusts T. Sullivan overall

1. Rohit Tripathy
2. Yibo Yang
3. Paris Perdikaris
4. Jon Cockayne
5. Ilias Bilionis
6. Sharmila Karumuri
7. Warrren B Powell
8. Maizar Raissi

Papers from T. Sullivan's perspective

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

1. Inverse problems: A Bayesian perspective (Acta Numerica)
2. Statistical Decision Theory and Bayesian Analysis, Second Edition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Feynman-Kac Formulae: Genealogical and Interacting Particle Systems with Applications
5. Bayesian Interpolation
6. A New Approach to Probabilistic Programming Inference
7. ImageNet classification with deep convolutional neural networks
8. A Correspondence Between Bayesian Estimation on Stochastic Processes and Smoothing by Splines
9. Church: a language for generative models
10. Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes

Their papers

• Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems (2016) — 47 citations
• Bayesian Probabilistic Numerical Methods (2017) — 182 citations
• Introduction to Uncertainty Quantification (2015) — 501 citations