Scott Fujimoto

3.8k total citations
6 papers, 191 citations indexed

About

Scott Fujimoto is a scholar working on Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering. According to data from OpenAlex, Scott Fujimoto has authored 6 papers receiving a total of 191 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 1 paper in Computer Networks and Communications and 1 paper in Control and Systems Engineering. Recurrent topics in Scott Fujimoto's work include Reinforcement Learning in Robotics (2 papers), Topic Modeling (1 paper) and Advanced Text Analysis Techniques (1 paper). Scott Fujimoto is often cited by papers focused on Reinforcement Learning in Robotics (2 papers), Topic Modeling (1 paper) and Advanced Text Analysis Techniques (1 paper). Scott Fujimoto collaborates with scholars based in Canada, Netherlands and Sweden. Scott Fujimoto's co-authors include David Meger, Herke van Hoof, Adriana Romero, Edward J. Smith, Eisha Ahmed, Derek Ruths, Gregory Dudek, Francois R. Hogan and Doina Precup and has published in prestigious journals such as UvA-DARE (University of Amsterdam), arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Scott Fujimoto

4 papers receiving 184 citations

Peers

Scott Fujimoto

AI

CSE

EEE

CVPR

AE

Matthieu Geist France

Junhyuk Oh United States

Gereon Weiß Germany

Jacek M. Czerniak Poland

Ricardo Martínez Mexico

Fabio Pardo United Kingdom

Prateek Singhal India

Zhen Gao China

Yunlong Mao China

Seungil You United States

Matthieu Geist France

Scott Fujimoto

176 ×1.5

AI

52 ×1.0

CSE

25 ×0.7

EEE

29 ×0.8

CVPR

10 ×0.4

AE

Citations per year, relative to Scott Fujimoto Scott Fujimoto (= 1×) peers Matthieu Geist

Countries citing papers authored by Scott Fujimoto

Since Specialization

Citations

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

Fields of papers citing papers by Scott Fujimoto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Scott Fujimoto

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

All Works

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6 of 6 papers shown

1.

Hogan, Francois R., et al.. (2025). Generalizable Imitation Learning Through Pre-Trained Representations. 1–8.

2.

Fujimoto, Scott. (2024). Off-Policy Deep Reinforcement Learning without Exploration. International Conference on Machine Learning. 2052–2062.

3.

Fujimoto, Scott, David Meger, & Doina Precup. (2021). A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation. arXiv (Cornell University). 3518–3529. 1 indexed citations

4.

Smith, Edward J., Scott Fujimoto, Adriana Romero, & David Meger. (2019). GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. arXiv (Cornell University). 5866–5876. 15 indexed citations

5.

Fujimoto, Scott, Herke van Hoof, & David Meger. (2018). Addressing Function Approximation Error in Actor-Critic Methods. UvA-DARE (University of Amsterdam). 80. 1587–1596. 143 indexed citations

6.

Ahmed, Eisha, et al.. (2018). Sentiment Analysis: It’s Complicated!. 1886–1895. 32 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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