Antonietta Mira
Statistics and Probability · 2001–2015
A researcher in the Science corpus: 11 papers; trusts 68 researchers and is trusted by 56 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 66 citations into it; #1,056 of 12,932 by trust here, #1,100 by citations
- Artificial Intelligence — 42 citations into it; #4,826 of 35,345 by trust here, #7,310 by citations
- Probabilistic & Bayesian Methods — 33 citations into it; #1,172 of 1,525 by trust here, #1,274 by citations
- Mathematical Physics — 13 citations into it; #843 of 8,562 by trust here, #773 by citations
- Statistical and Nonlinear Physics — 8 citations into it
- Finance — 7 citations into it
- Economics and Econometrics — 5 citations into it
- Molecular Biology — 5 citations into it; #2,797 of 17,773 by trust here, #12,227 by citations
Whom Antonietta Mira trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Gareth O. Roberts
- Peter J. Green
- Julian Besag
- David Ardia
- Jim Albert
- Mark A. Girolami
- Tim Bollerslev
- Ben Calderhead
- Michel Caffarel
- Christian P. Robert
Who trusts Antonietta Mira overall
- Chris J. Oates
- Theodore Papamarkou
- Xun Huan
- Mark A. Girolami
- Nial Friel
- Benjamin Peherstorfer
- Mylene B'edard
- Youssef M. Marzouk
- Antti Solonen
- Galin L. Jones
Papers from Antonietta Mira's perspective
Ordered by how strongly the researchers Antonietta Mira trusts endorse each paper. Same corpus, a different order for every researcher.
- Sampling-Based Approaches to Calculating Marginal Densities
- Sequential Monte Carlo samplers
- Riemann manifold Langevin and Hamiltonian Monte Carlo methods
- Monte Carlo Sampling Methods Using Markov Chains and Their Applications
- Monte Carlo Strategies in Scientific Computing
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Monte Carlo Statistical Methods
- Learning Multiple Layers of Features from Tiny Images
- ImageNet classification with deep convolutional neural networks
- The pseudo-marginal approach for efficient Monte Carlo computations
Their papers
- Perfect slice samplers (2001) — 82 citations
- DRAM: Efficient adaptive MCMC (2006) — 1,535 citations
- Adaptive Multiple Importance Sampling (2009) — 286 citations
- Delayed rejection in reversible jump Metropolis–Hastings (2001) — 309 citations
- Efficiency and Convergence Properties of Slice Samplers (2002) — 96 citations
- Zero Variance Differential Geometric Markov Chain Monte Carlo Algorithms (2014) — 37 citations
- Zero variance Markov chain Monte Carlo for Bayesian estimators (2010) — 97 citations
- Exploiting Multi-Core Architectures for Reduced-Variance Estimation with Intractable Likelihoods (2014) — 26 citations
- Monte Carlo methods and zero variance principle (2015)
- Efficient Bayes factor estimation from the reversible jump output (2006) — 58 citations
- On Metropolis-Hastings algorithms with delayed rejection (2001) — 202 citations