Luca Franceschi
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Artificial Intelligence
- Control and Systems Engineering
- Aerospace Engineering
- Co-authors
- Massimiliano PontilDarwin G. CaldwellMichele FocchiClaudio SeminiMarco CamurriVictor BarasuolMathias NiepertXiao He
- Topics
- Machine Learning and Algorithms (2 papers)Explainable Artificial Intelligence (XAI) (2 papers)Robotic Locomotion and Control (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionBiomedical EngineeringControl and Systems Engineering
- Journals
- IEEE Robotics and Automation LettersHAL (Le Centre pour la Communication Scientifique Directe)Florence Research (University of Florence)
- Partner nations
- ItalyUnited KingdomGermany
In The Last Decade
Luca Franceschi
10 papers receiving 75 citations
Peers
Comparison fields: 5 of 35
- Biomedical Engineering 42
- Computer Vision and Pattern Recognition 32
- Artificial Intelligence 23
- Control and Systems Engineering 17
- Aerospace Engineering 17
Countries citing papers authored by Luca Franceschi
This map shows the geographic impact of Luca Franceschi'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 Luca Franceschi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luca Franceschi more than expected).
Fields of papers citing papers by Luca Franceschi
This network shows the impact of papers produced by Luca Franceschi. 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 Luca Franceschi. The network helps show where Luca Franceschi may publish in the future.
Co-authorship network of co-authors of Luca Franceschi
This figure shows the co-authorship network connecting the top 25 collaborators of Luca Franceschi. A scholar is included among the top collaborators of Luca Franceschi 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 Luca Franceschi. Luca Franceschi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | On the Iteration Complexity of Hypergradient Computations | 1 |
| 5 | Learning Discrete Structures for Graph Neural Networks | 14 |
| 6 | Scheduling the Learning Rate Via Hypergradients: New Insights and a New Algorithm | 1 |
| 7 | 48 | |
| 8 | Fast and Continuous Foothold Adaptation for Dynamic Locomotion through Convolutional Neural Networks. | 1 |
| 9 | On Hyperparameter Optimization in Learning Systems. | 4 |
| 10 | 3 |
About Luca Franceschi
Luca Franceschi is a scholar working on Health Informatics, Algebra and Number Theory and Artificial Intelligence, having authored 10 papers that have together received 77 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (2 papers), Explainable Artificial Intelligence (XAI) (2 papers) and Robotic Locomotion and Control (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (32 citations), Biomedical Engineering (42 citations) and Control and Systems Engineering (17 citations). Luca Franceschi has collaborated with scholars based in Italy, United Kingdom and Germany. Frequent co-authors include Massimiliano Pontil, Darwin G. Caldwell, Michele Focchi, Claudio Semini, Marco Camurri, Victor Barasuol, Mathias Niepert, Xiao He, Michele Donini and Paolo Frasconi. Their work appears in journals such as IEEE Robotics and Automation Letters, HAL (Le Centre pour la Communication Scientifique Directe) and Florence Research (University of Florence).
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.