Countries citing papers authored by Raphaël Fonteneau
Since
Specialization
Citations
This map shows the geographic impact of Raphaël Fonteneau'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 Raphaël Fonteneau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël Fonteneau more than expected).
Fields of papers citing papers by Raphaël Fonteneau
This network shows the impact of papers produced by Raphaël Fonteneau. 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 Raphaël Fonteneau. The network helps show where Raphaël Fonteneau may publish in the future.
Co-authorship network of co-authors of Raphaël Fonteneau
This figure shows the co-authorship network connecting the top 25 collaborators of Raphaël Fonteneau.
A scholar is included among the top collaborators of Raphaël Fonteneau 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 Raphaël Fonteneau. Raphaël Fonteneau is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Ernst, Damien, et al.. (2020). The Role of Hydrogen in the Dutch Electricity System. Open Repository and Bibliography (University of Liège).1 indexed citations
6.
Frédéric, Olivier, et al.. (2017). Foreseeing New Control Challenges in Electricity Prosumer Communities. Open Repository and Bibliography (University of Liège).11 indexed citations
7.
François-Lavet, Vincent, et al.. (2016). Deep Reinforcement Learning Solutions for Energy Microgrids Management. Open Repository and Bibliography (University of Liège).98 indexed citations
François-Lavet, Vincent, Raphaël Fonteneau, & Damien Ernst. (2014). Using approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device.1 indexed citations
10.
Ernst, Damien, et al.. (2014). Bayes Adaptive Reinforcement Learning versus Off-line Prior-based Policy Search: an Empirical Comparison.2 indexed citations
Maes, Frederik, et al.. (2012). Learning Exploration/Exploitation Strategies for Single Trajectory Reinforcement Learning. Open Repository and Bibliography (University of Liège). 1–10.14 indexed citations
Fonteneau, Raphaël, et al.. (2011). Artificial intelligence design for real-time strategy games. Open Repository and Bibliography (University of Liège).3 indexed citations
16.
Fonteneau, Raphaël, Damien Ernst, Bernard Boigelot, & Quentin Louveaux. (2011). Relaxation schemes for min max generalization in deterministic batch mode reinforcement learning. Open Repository and Bibliography (University of Liège).1 indexed citations
17.
Fonteneau, Raphaël, Susan A. Murphy, Louis Wehenkel, & Damien Ernst. (2010). Computing bounds for kernel-based policy evaluation in reinforcement learning. Open Repository and Bibliography (University of Liège).2 indexed citations
18.
Fonteneau, Raphaël, Susan A. Murphy, Louis Wehenkel, & Damien Ernst. (2010). Model-Free Monte Carlo-like Policy Evaluation. Journal of Machine Learning Research. 9. 217–224.6 indexed citations
19.
Fonteneau, Raphaël, Susan A. Murphy, Louis Wehenkel, & Damien Ernst. (2009). Dynamic treatment regimes using reinforcement learning: a cautious generalization approach. Open Repository and Bibliography (University of Liège).1 indexed citations
20.
Fonteneau, Raphaël, Louis Wehenkel, & Damien Ernst. (2008). Variable selection for dynamic treatment regimes: a reinforcement learning approach. Open Repository and Bibliography (University of Liège).11 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.