Luca Baldassarre
- Computational Mechanics top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Mathematical Physics top 10%
- Cognitive Neuroscience
- Co-authors
- Alessandro VerriMassimiliano PontilSilvia VillaSaverio SalzoJanaı́na Mourão-MirandaVolkan CevherGuy LeverArthur Gretton
- Topics
- Sparse and Compressive Sensing Techniques (13 papers)Blind Source Separation Techniques (4 papers)Statistical Methods and Inference (3 papers)
- Partner nations
- SwitzerlandUnited KingdomUnited States
In The Last Decade
Luca Baldassarre
20 papers receiving 403 citations
Peers
Comparison fields: 5 of 78
- Computational Mechanics 201
- Artificial Intelligence 136
- Computer Vision and Pattern Recognition 70
- Mathematical Physics 60
- Cognitive Neuroscience 60
Countries citing papers authored by Luca Baldassarre
This map shows the geographic impact of Luca Baldassarre'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 Baldassarre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luca Baldassarre more than expected).
Fields of papers citing papers by Luca Baldassarre
This network shows the impact of papers produced by Luca Baldassarre. 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 Baldassarre. The network helps show where Luca Baldassarre may publish in the future.
Co-authorship network of co-authors of Luca Baldassarre
This figure shows the co-authorship network connecting the top 25 collaborators of Luca Baldassarre. A scholar is included among the top collaborators of Luca Baldassarre 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 Baldassarre. Luca Baldassarre is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 12 | |
| 4 | 24 | |
| 5 | 48 | |
| 6 | 4 | |
| 7 | 6 | |
| 8 | 32 | |
| 9 | Tractability of Interpretability via Selection of Group-Sparse Models | 2 |
| 10 | 25 | |
| 11 | 2 | |
| 12 | 0 | |
| 13 | 117 | |
| 14 | A General Framework for Structured Sparsity via Proximal Optimization | 7 |
| 15 | Conditional mean embeddings as regressors | 41 |
| 16 | Modelling transition dynamics in MDPs with RKHS embeddings | 28 |
| 17 | 37 | |
| 18 | 28 | |
| 19 | Towards a Theoretical Framework for Learning Multi-modal Patterns for Embodied Agents | 0 |
| 20 | 3 |
About Luca Baldassarre
Luca Baldassarre is a scholar working on Computational Mechanics, Statistics and Probability and Signal Processing, having authored 23 papers that have together received 424 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (13 papers), Blind Source Separation Techniques (4 papers) and Statistical Methods and Inference (3 papers). The work is most often cited by research in Numerical Analysis (54 citations), Computational Mechanics (201 citations) and Mathematical Physics (60 citations). Luca Baldassarre has collaborated with scholars based in Switzerland, United Kingdom and United States. Frequent co-authors include Alessandro Verri, Massimiliano Pontil, Silvia Villa, Saverio Salzo, Janaı́na Mourão-Miranda, Volkan Cevher, Guy Lever, Arthur Gretton, Jonathan Scarlett and Ilija Bogunovic. Their work appears in journals such as IEEE Signal Processing Magazine, Machine Learning and Frontiers in Neuroscience.
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.