Michael Riis Andersen

418 total citations
19 papers, 130 citations indexed

About

Michael Riis Andersen is a scholar working on Artificial Intelligence, Computational Mechanics and Statistics and Probability. According to data from OpenAlex, Michael Riis Andersen has authored 19 papers receiving a total of 130 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 4 papers in Computational Mechanics and 4 papers in Statistics and Probability. Recurrent topics in Michael Riis Andersen's work include Gaussian Processes and Bayesian Inference (11 papers), Sparse and Compressive Sensing Techniques (4 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). Michael Riis Andersen is often cited by papers focused on Gaussian Processes and Bayesian Inference (11 papers), Sparse and Compressive Sensing Techniques (4 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). Michael Riis Andersen collaborates with scholars based in Denmark, Finland and Germany. Michael Riis Andersen's co-authors include Lars Kai Hansen, Ole Winther, Aki Vehtari, Ib Chorkendorff, Martin Johansson, Paul‐Christian Bürkner, Arno Solin, Javier González, Johan Jonasson and Måns Magnusson and has published in prestigious journals such as The Journal of Physical Chemistry B, Journal of Machine Learning Research and Heliyon.

In The Last Decade

Michael Riis Andersen

15 papers receiving 125 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael Riis Andersen Denmark 6 32 23 22 17 15 19 130
Pierre Calka France 9 32 1.0× 14 0.6× 7 0.3× 19 1.1× 11 0.7× 27 212
P. Kubinec Slovakia 6 10 0.3× 33 1.4× 4 0.2× 13 0.8× 29 1.9× 29 117
Oswin Krause Denmark 8 71 2.2× 7 0.3× 6 0.3× 12 0.7× 21 1.4× 20 144
Stephan Thaler Germany 7 21 0.7× 76 3.3× 6 0.3× 16 0.9× 7 0.5× 13 167
Xiaohu Liu United States 9 157 4.9× 23 1.0× 24 1.1× 6 0.4× 25 1.7× 30 234
Viraj Shah United States 7 11 0.3× 4 0.2× 46 2.1× 21 1.2× 55 3.7× 17 143
Sebastian Lunz United Kingdom 5 35 1.1× 7 0.3× 18 0.8× 10 0.6× 50 3.3× 7 138
Wilhelm Forst Germany 4 25 0.8× 3 0.1× 16 0.7× 17 1.0× 3 0.2× 15 123
Tianchen Zhao China 6 53 1.7× 18 0.8× 5 0.2× 8 0.5× 29 1.9× 23 111
A. Ustyuzhanin Russia 7 39 1.2× 61 2.7× 29 1.7× 8 0.5× 46 186

Countries citing papers authored by Michael Riis Andersen

Since Specialization
Citations

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

Fields of papers citing papers by Michael Riis Andersen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Riis Andersen. 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 Michael Riis Andersen. The network helps show where Michael Riis Andersen may publish in the future.

Co-authorship network of co-authors of Michael Riis Andersen

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Riis Andersen. A scholar is included among the top collaborators of Michael Riis Andersen 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 Michael Riis Andersen. Michael Riis Andersen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
1.
Andersen, Michael Riis, et al.. (2024). NMR-Onion - a transparent multi-model based 1D NMR deconvolution algorithm. Heliyon. 10(17). e36998–e36998. 1 indexed citations
2.
Polignano, Marco, et al.. (2024). EB-NeRD a large-scale dataset for news recommendation. arXiv (Cornell University). 1–11. 5 indexed citations
3.
4.
Andersen, Michael Riis, et al.. (2023). Automatic proficiency scoring for early-stage writing. Computers and Education Artificial Intelligence. 5. 100168–100168. 2 indexed citations
5.
Bürkner, Paul‐Christian, et al.. (2022). Practical Hilbert space approximate Bayesian Gaussian processes for probabilistic programming. Statistics and Computing. 33(1). 23 indexed citations
6.
Andersen, Michael Riis, et al.. (2021). When Did the Train Arrive? A Bayesian Approach to Enrich Timetable Information Using Smart Card Data. IEEE Open Journal of Intelligent Transportation Systems. 2. 160–172. 2 indexed citations
7.
Andersen, Michael Riis, et al.. (2021). Preferential Batch Bayesian Optimization. Aaltodoc (Aalto University). 1–6. 4 indexed citations
8.
Magnusson, Måns, Aki Vehtari, Johan Jonasson, & Michael Riis Andersen. (2020). Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large Data. Chalmers Research (Chalmers University of Technology). 108. 341–351. 2 indexed citations
9.
Wilkinson, William J., et al.. (2020). State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes. arXiv (Cornell University). 1. 10270–10281.
10.
Andersen, Michael Riis, et al.. (2020). Scalable Gaussian Process for Extreme Classification. Aaltodoc (Aalto University). 38. 1–6.
11.
Magnusson, Måns, Michael Riis Andersen, & Johan Jonasson. (2019). Bayesian leave-one-out cross-validation for large data. arXiv (Cornell University). 7505–7525. 3 indexed citations
12.
Andersen, Michael Riis, Ole Winther, Lars Kai Hansen, Russell A. Poldrack, & Oluwasanmi Koyejo. (2018). Bayesian structure learning for dynamic brain connectivity. Aaltodoc (Aalto University). 1436–1446. 4 indexed citations
13.
Vehtari, Aki, et al.. (2018). CORRECTING BOUNDARY OVER-EXPLORATION DEFICIENCIES IN BAYESIAN OPTIMIZATION WITH VIRTUAL DERIVATIVE SIGN OBSERVATIONS. Työväentutkimus Vuosikirja. 1–6. 6 indexed citations
14.
Meng, Xiangming, Sheng Wu, Michael Riis Andersen, Jiang Zhu, & Zuyao Ni. (2018). Efficient recovery of structured sparse signals via approximate message passing with structured spike and slab prior. China Communications. 15(6). 1–17. 6 indexed citations
15.
Andersen, Michael Riis, Aki Vehtari, Ole Winther, & Lars Kai Hansen. (2017). Bayesian Inference for Spatio-temporal Spike-and-Slab Priors. Journal of Machine Learning Research. 18(139). 1–58. 17 indexed citations
16.
Andersen, Michael Riis, Ole Winther, & Lars Kai Hansen. (2014). Bayesian Inference for Structured Spike and Slab Priors. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 27. 1745–1753. 26 indexed citations
17.
Andersen, Michael Riis. (2014). Sparse inference using approximate message passing. 3 indexed citations
18.
Andersen, Michael Riis, et al.. (2013). Learning the solution sparsity of an ill-posed linear inverse problem with the Variational Garrote. 1–6. 1 indexed citations
19.
Andersen, Michael Riis, Martin Johansson, & Ib Chorkendorff. (2005). Isotopic Exchange of CO Adsorbed on Pt(111). The Journal of Physical Chemistry B. 109(20). 10285–10290. 25 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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