Christopher Nemeth

468 total citations
22 papers, 201 citations indexed

About

Christopher Nemeth is a scholar working on Artificial Intelligence, Statistics and Probability and Statistical and Nonlinear Physics. According to data from OpenAlex, Christopher Nemeth has authored 22 papers receiving a total of 201 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 8 papers in Statistics and Probability and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Christopher Nemeth's work include Bayesian Methods and Mixture Models (8 papers), Markov Chains and Monte Carlo Methods (7 papers) and Gaussian Processes and Bayesian Inference (7 papers). Christopher Nemeth is often cited by papers focused on Bayesian Methods and Mixture Models (8 papers), Markov Chains and Monte Carlo Methods (7 papers) and Gaussian Processes and Bayesian Inference (7 papers). Christopher Nemeth collaborates with scholars based in United Kingdom, United States and Netherlands. Christopher Nemeth's co-authors include Paul Fearnhead, Lyudmila Mihaylova, Jan Melchior van Wessem, Johanni Brea, Emily B. Fox, Peter Kuipers Munneke, Amber Leeson, Vincent Verjans, C. Max Stevens and Brice Noël and has published in prestigious journals such as Journal of the American Statistical Association, Scientific Reports and IEEE Transactions on Signal Processing.

In The Last Decade

Christopher Nemeth

18 papers receiving 195 citations

Peers

Christopher Nemeth
Comparison fields: 5 of 74
  • Artificial Intelligence 101
  • Statistics and Probability 45
  • Control and Systems Engineering 33
  • Statistical and Nonlinear Physics 16
  • Atmospheric Science 15
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Citations per field, relative to Christopher Nemeth
Christopher Nemeth · 1×
Citations per year, relative to Christopher Nemeth
Christopher Nemeth · 1×

Countries citing papers authored by Christopher Nemeth

Since Specialization
Citations

This map shows the geographic impact of Christopher Nemeth'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 Christopher Nemeth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Nemeth more than expected).

Fields of papers citing papers by Christopher Nemeth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher Nemeth. 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 Christopher Nemeth. The network helps show where Christopher Nemeth may publish in the future.

Co-authorship network of co-authors of Christopher Nemeth

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Nemeth. A scholar is included among the top collaborators of Christopher Nemeth 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 Christopher Nemeth. Christopher Nemeth 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
# Work Indexed citations
1 0
2 1
3 1
4 0
5 5
6 1
7 2
8 1
9 3
10 12
11 65
12
Latent Space Representations of Hypergraphs
0
13 6
14
Large-Scale Stochastic Sampling from the Probability Simplex
2
15 14
16 59
17 6
18
Bearings-only tracking with particle filtering for joint parameter learning and state estimation
1
19 10
20
Hidden Markov Models with Applications to DNA Sequence Analysis
0

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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