Mathieu Sinn

32 papers receiving 496 citations

Peers

Mathieu Sinn
Comparison fields: 5 of 92
  • Statistical and Nonlinear Physics 139
  • Signal Processing 86
  • Transportation 46
  • Building and Construction 73
  • Economics and Econometrics 145
Replace Masahiro Takatsuka with:
Masahiro Takatsuka Australia
Shuai Xiao China
Geoffrey Yeo Australia
Yu Lu China
Snehanshu Saha India
Mario Manzo Italy
Juan Chen China
Daniel Defays Belgium
Qingyong Wang China
Mathieu Sinn relative to Masahiro Takatsuka Australia Masahiro Takatsuka's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mathieu Sinn

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu Sinn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mathieu Sinn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mathieu Sinn Line = papers co-authored together Mathieu Sinn links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200596
2 201158
3 200743
4 201342
5 201241
6 201038
7 201032
8 201324
9
Adaptive Learning of Smoothing Functions: Application to Electricity Load Forecasting
201223
10 200915
11 201311
12 201411
13
Forecasting Uncertainty in Electricity Demand
201510
14 20169
15 20119
16 20137
17 20127
18
Asymptotic Theory for Linear-Chain Conditional Random Fields
20116
19 20126
20 20165

About Mathieu Sinn

Mathieu Sinn is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Economics and Econometrics, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 32 papers that have together received 521 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (10 papers), Complex Systems and Time Series Analysis (8 papers), Chaos control and synchronization (6 papers), Time Series Analysis and Forecasting (5 papers), Anomaly Detection Techniques and Applications (4 papers), Context-Aware Activity Recognition Systems (3 papers), Financial Risk and Volatility Modeling (3 papers) and Smart Grid Energy Management (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (139 citations), Signal Processing (86 citations), Transportation (46 citations), Building and Construction (73 citations) and Economics and Econometrics (145 citations). Mathieu Sinn has collaborated with scholars based in Ireland, United States and Canada. Frequent co-authors include Karsten Keller, Carlos Alzate, Francesco Calabrese, Johannes Textor, Ji Won Yoon, Jürgen Westermann, Eric Bouillet, Ulrich H. von Andrian, Sarah E. Henrickson and António Peixoto. Their work appears in journals such as IBM Journal of Research and Development, Computational Statistics & Data Analysis, BMC Bioinformatics, Physica A Statistical Mechanics and its Applications and Stochastics and Dynamics.

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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