Fabio Viola
- Computer Vision and Pattern Recognition
- Civil and Structural Engineering
- Geology top 10%
- Environmental Engineering
- Aerospace Engineering
- Co-authors
- Kenichi SogaRoberto CipollaTae‐Kyun KimKrisada ChaiyasarnWenbin LiGabriel BrostowNeill D. F. CampbellJ. Starck
- Topics
- 3D Surveying and Cultural Heritage (3 papers)Image and Object Detection Techniques (3 papers)Reinforcement Learning in Robotics (3 papers)
- Journals
- ACM Transactions on GraphicsJournal of Computing in Civil EngineeringarXiv (Cornell University)
- Partner nations
- United KingdomUnited StatesThailand
In The Last Decade
Fabio Viola
7 papers receiving 94 citations
Peers
Comparison fields: 5 of 34
- Computer Vision and Pattern Recognition 43
- Civil and Structural Engineering 40
- Geology 40
- Environmental Engineering 24
- Aerospace Engineering 9
Countries citing papers authored by Fabio Viola
This map shows the geographic impact of Fabio Viola'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 Fabio Viola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabio Viola more than expected).
Fields of papers citing papers by Fabio Viola
This network shows the impact of papers produced by Fabio Viola. 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 Fabio Viola. The network helps show where Fabio Viola may publish in the future.
Co-authorship network of co-authors of Fabio Viola
This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Viola. A scholar is included among the top collaborators of Fabio Viola 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 Fabio Viola. Fabio Viola is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | On the role of planning in model-based deep reinforcement learning | 10 |
| 2 | Value-driven Hindsight Modelling | 1 |
| 3 | Learning Dynamic State Abstractions for Model-Based Reinforcement Learning | 1 |
| 4 | Learning to encode spatial relations from natural language | 2 |
| 5 | 0 | |
| 6 | 26 | |
| 7 | 47 | |
| 8 | 11 |
About Fabio Viola
Fabio Viola is a scholar working on Geology, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 98 indexed citations. Recurring topics across this work include 3D Surveying and Cultural Heritage (3 papers), Image and Object Detection Techniques (3 papers) and Reinforcement Learning in Robotics (3 papers). The work is most often cited by research in Geology (40 citations), Computer Vision and Pattern Recognition (43 citations) and Civil and Structural Engineering (40 citations). Fabio Viola has collaborated with scholars based in United Kingdom, United States and Thailand. Frequent co-authors include Kenichi Soga, Roberto Cipolla, Tae‐Kyun Kim, Krisada Chaiyasarn, Wenbin Li, Gabriel Brostow, Neill D. F. Campbell, J. Starck, Jessica B. Hamrick and Théophane Weber. Their work appears in journals such as ACM Transactions on Graphics, Journal of Computing in Civil Engineering and arXiv (Cornell University).
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.