M. Pitt

14.3k total citations · 2 hit papers
43 papers, 3.4k citations indexed

About

M. Pitt is a scholar working on Finance, Nuclear and High Energy Physics and Statistics and Probability. According to data from OpenAlex, M. Pitt has authored 43 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Finance, 12 papers in Nuclear and High Energy Physics and 12 papers in Statistics and Probability. Recurrent topics in M. Pitt's work include Financial Risk and Volatility Modeling (13 papers), Particle Detector Development and Performance (10 papers) and Bayesian Methods and Mixture Models (8 papers). M. Pitt is often cited by papers focused on Financial Risk and Volatility Modeling (13 papers), Particle Detector Development and Performance (10 papers) and Bayesian Methods and Mixture Models (8 papers). M. Pitt collaborates with scholars based in United Kingdom, Israel and Australia. M. Pitt's co-authors include Neil Shephard, Robert Kohn, David Chan, Randal Douc, Paolo Giordani, George Deligiannidis, Sheheryar Malik, Adrian Banning, Peter M. Schofield and Adam de Belder and has published in prestigious journals such as New England Journal of Medicine, Journal of the American Statistical Association and Journal of the American College of Cardiology.

In The Last Decade

M. Pitt

41 papers receiving 3.2k citations

Hit Papers

Filtering via Simulation: Auxiliary Particle Filters 1999 2026 2008 2017 1999 1999 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
M. Pitt United Kingdom 18 1.6k 564 505 358 354 43 3.4k
Anestis Antoniadis France 32 557 0.4× 253 0.4× 1.0k 2.0× 477 1.3× 186 0.5× 110 3.9k
R. Douglas Martin United States 23 1.4k 0.9× 449 0.8× 2.2k 4.3× 40 0.1× 341 1.0× 77 5.3k
Patrice Abry France 39 966 0.6× 715 1.3× 131 0.3× 424 1.2× 1.7k 4.8× 247 5.7k
Rong Chen United States 22 1.1k 0.7× 572 1.0× 729 1.4× 17 0.0× 569 1.6× 76 3.3k
Hao Helen Zhang United States 32 983 0.6× 99 0.2× 1.9k 3.7× 54 0.2× 232 0.7× 114 4.5k
Jun Fan China 20 361 0.2× 113 0.2× 560 1.1× 548 1.5× 179 0.5× 91 2.1k
Guy P. Nason United Kingdom 26 330 0.2× 221 0.4× 332 0.7× 161 0.4× 387 1.1× 97 2.7k
Vladimír Beneš Czechia 33 358 0.2× 519 0.9× 177 0.4× 106 0.3× 186 0.5× 234 4.9k
Theofanis Sapatinas Cyprus 20 585 0.4× 168 0.3× 553 1.1× 61 0.2× 171 0.5× 61 2.9k
Christian Weiß Germany 35 590 0.4× 1.3k 2.2× 1.7k 3.5× 1.1k 3.1× 370 1.0× 234 4.6k

Countries citing papers authored by M. Pitt

Since Specialization
Citations

This map shows the geographic impact of M. Pitt's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by M. Pitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Pitt more than expected).

Fields of papers citing papers by M. Pitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Pitt. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by M. Pitt. The network helps show where M. Pitt may publish in the future.

Co-authorship network of co-authors of M. Pitt

This figure shows the co-authorship network connecting the top 25 collaborators of M. Pitt. A scholar is included among the top collaborators of M. Pitt based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with M. Pitt. M. Pitt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Pitt, M.. (2024). Physics perspectives of a CMS near-beam proton spectrometer at the HL-LHC. arXiv (Cornell University). 12–12. 1 indexed citations
2.
Pitt, M.. (2023). Physics at the HL-LHC with Proton Tagging. Acta Physica Polonica B Proceedings Supplement. 16(7). 1–1. 1 indexed citations
4.
Pitt, M.. (2023). Diffractive and Photon-Induced Production of Top Quark. Universe. 9(11). 483–483. 1 indexed citations
5.
Malawski, M., et al.. (2022). A Serverless Engine for High Energy Physics Distributed Analysis. arXiv (Cornell University). 575–584. 3 indexed citations
6.
Deligiannidis, George, Sebastian M. Schmon, Randal Douc, & M. Pitt. (2020). Large sample asymptotics of the pseudo-marginal method. Research Portal (King's College London). 12 indexed citations
7.
Correia, P. M. M., M. Pitt, C.D.R. Azevedo, et al.. (2018). Simulation of gain stability of THGEM gas-avalanche particle detectors. Journal of Instrumentation. 13(1). P01015–P01015. 16 indexed citations
8.
Hall, Jamie, M. Pitt, & Robert Kohn. (2014). Bayesian inference for nonlinear structural time series models. Journal of Econometrics. 179(2). 99–111. 8 indexed citations
9.
Pitt, M., et al.. (2014). Bayesian Inference for a Semi-Parametric Copula-based Markov Chain. The Warwick Economics Research Paper Series (TWERPS). 1 indexed citations
10.
Tran, Minh‐Ngoc, et al.. (2014). Importance Sampling Squared for Bayesian Inference in Latent Variable Models. SSRN Electronic Journal. 26 indexed citations
11.
Bressler, S., L. Arazi, L. Moleri, et al.. (2013). Recent advances with THGEM detectors. Journal of Instrumentation. 8(12). C12012–C12012. 13 indexed citations
12.
Pitt, M., Ralph Silva, Paolo Giordani, & Robert Kohn. (2012). On Some Properties of Markov Chain Monte Carlo Simulation Methods Based on the Particle Filter. SSRN Electronic Journal. 4 indexed citations
13.
Malik, Sheheryar, et al.. (2009). Modelling Stochastic Volatility with Leverage and Jumps: A Simulated Maximum Likelihood Approach via Particle Filtering.. AgEcon Search (University of Minnesota, USA). 11 indexed citations
14.
Dutka, David P., M. Pitt, Duilio Pagano, et al.. (2006). Myocardial Glucose Transport and Utilization in Patients With Type 2 Diabetes Mellitus, Left Ventricular Dysfunction, and Coronary Artery Disease. Journal of the American College of Cardiology. 48(11). 2225–2231. 74 indexed citations
15.
Gershlick, AH, Susan M. Hughes, Keith R. Abrams, et al.. (2005). for the REACT Trial Investigators. Rescue Angioplasty after Failed Thrombolytic Therapy for Acute Myocardial Infarction. New England Journal of Medicine. 2758–2768. 35 indexed citations
16.
Gershlick, Anthony, Keith R. Abrams, Suzanne Stevens, et al.. (2005). Rescue Angioplasty after Failed Thrombolytic Therapy for Acute Myocardial Infarction. New England Journal of Medicine. 353(26). 2758–2768. 276 indexed citations
17.
Pitt, M., Chris Chatfield, & Stephen G. Walker. (2002). Constructing First Order Stationary Autoregressive Models via Latent Processes. Scandinavian Journal of Statistics. 29(4). 657–663. 39 indexed citations
18.
Pitt, M. & Neil Shephard. (1996). Analytic convergence rates and parameterisation issues for the Gibbs sampler applied to state space models. Oxford University Research Archive (ORA) (University of Oxford). 1 indexed citations
19.
Pitt, M., et al.. (1996). Hypereosinophilic syndrome: endomyocardial fibrosis.. Heart. 76(4). 377–378. 13 indexed citations
20.
Heckmatt, J Z, M. Pitt, & Fenella J. Kirkham. (1993). Peripheral Neuropathy and Neuromuscular Blockade Presenting as Prolonged Respiratory Paralysis Following Critical Illness. Neuropediatrics. 24(3). 123–125. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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