Edward L. Ionides

Artificial Intelligence · 2006–2015

A researcher in the Science corpus: 4 papers; trusts 44 researchers and is trusted by 43 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it; #3,696 of 35,345 by trust here, #13,353 by citations
• Statistics and Probability — 28 citations into it; #1,081 of 12,932 by trust here, #4,132 by citations
• Modeling and Simulation — 12 citations into it
• Probabilistic & Bayesian Methods — 11 citations into it
• Ecology — 10 citations into it
• Global and Planetary Change — 6 citations into it
• Public Health, Environmental and Occupational Health — 6 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Edward L. Ionides trusts overall

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

1. Tim Hesterberg
2. Colin L. Mallows
3. G. Oehlert
4. Jane Liu
5. OTTAR N. Bjørnstad
6. Bryan T. Grenfell
7. Bärbel F. Finkenstädt
8. David L. Donoho
9. Garland B. Durham
10. Olivier Capp'e

Who trusts Edward L. Ionides overall

1. Aki Vehtari
2. Yong Luo
3. Tor Lattimore
4. Artem Sokolov
5. Andrew Gelman
6. Katja Hofmann
7. M. M. Afsar
8. Onur Atan
9. Adith Swaminathan
10. Yuan Xie

Papers from Edward L. Ionides's perspective

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

1. Sequential Monte Carlo methods for dynamic systems
2. Novel approach to nonlinear/non-Gaussian Bayesian state estimation
3. Monte Carlo Strategies in Scientific Computing
4. Combined Parameter and State Estimation in Simulation-Based Filtering (Sequential Monte Carlo Methods in Practice)
5. Filtering via Simulation: Auxiliary Particle Filters
6. On inference for partially observed nonlinear diffusion models using the Metropolis–Hastings algorithm
7. Likelihood INference for Discretely Observed Non-linear Diffusions
8. The pseudo-marginal approach for efficient Monte Carlo computations
9. Particle filters for state-space models with the presence of unknown static parameters (IEEE Transactions on Signal Processing)
10. Comparison of resampling schemes for particle filtering

Their papers

• Truncated Importance Sampling (2008) — 252 citations
• Statistical Inference for Partially Observed Markov Processes via the R Package pomp (2015) — 356 citations
• Plug-and-play inference for disease dynamics: measles in large and small populations as a case study (2009) — 308 citations
• Inference for nonlinear dynamical systems (2006) — 518 citations