Simon J. Godsill

Artificial Intelligence · 2000–2007

A researcher in the Science corpus: 8 papers; trusts 51 researchers and is trusted by 135 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it; #2,193 of 35,345 by trust here, #4,602 by citations
• Probabilistic & Bayesian Methods — 39 citations into it; #215 of 1,525 by trust here, #259 by citations
• Statistics and Probability — 23 citations into it; #509 of 12,932 by trust here, #830 by citations
• Computer Networks and Communications — 8 citations into it; #5,980 of 9,886 by trust here, #8,543 by citations
• Oceanography — 5 citations into it; #445 of 4,047 by trust here, #1,901 by citations
• Signal Processing — 5 citations into it; #1,776 of 7,572 by trust here, #3,099 by citations

Whom Simon J. Godsill trusts overall

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

1. Peter J. Green
2. Arnaud Doucet
3. Alexander Shapiro
4. Neil J. Gordon
5. Jun S. Liu
6. Stuart Geman
7. Alan E. Gelfand
8. Adrian F. M. Smith
9. Walter R. Gilks
10. Michael K. Pitt

Who trusts Simon J. Godsill overall

1. Arnaud Doucet
2. Fredrik Lindsten
3. Jaco Vermaak
4. Nial Friel
5. David I. Hastie
6. Steve P. Brooks
7. Hedibert Freitas Lopes
8. Thomas Bo Schön
9. Xin Zhao
10. Christophe Andrieu

Papers from Simon J. Godsill's perspective

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

1. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
2. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
3. A tutorial on hidden Markov models and selected applications in speech recognition
4. Novel approach to nonlinear/non-Gaussian Bayesian state estimation
5. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
6. Following a moving target—Monte Carlo inference for dynamic Bayesian models
7. Sequential Monte Carlo Methods in Practice
8. Sequential Monte Carlo methods for dynamic systems
9. Monte Carlo strategies in scientific computing
10. Filtering via Simulation: Auxiliary Particle Filters

Their papers

• On sequential Monte Carlo sampling methods for Bayesian filtering (2000) — 4,949 citations
• Monte Carlo Smoothing for Nonlinear Time Series (2004) — 638 citations
• An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo (2007) — 1,089 citations
• On the Relationship Between Markov chain Monte Carlo Methods for Model Uncertainty (2001) — 296 citations
• Poisson models for extended target and group tracking (2005) — 312 citations
• Monte Carlo filtering for multi target tracking and data association (2005) — 437 citations
• Reversible Jump Markov Chain Monte Carlo Strategies for Bayesian Model Selection in Autoregressive Processes (2004) — 81 citations
• Trans-dimensional Markov chain Monte Carlo (2000) — 364 citations