Marco Mondelli
About
In The Last Decade
Marco Mondelli
29 papers receiving 427 citations
Peers
Comparison fields: 5 of 41
- Computer Networks and Communications 351
- Electrical and Electronic Engineering 270
- Artificial Intelligence 181
- Molecular Biology 151
- Computational Theory and Mathematics 56
Countries citing papers authored by Marco Mondelli
This map shows the geographic impact of Marco Mondelli'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 Marco Mondelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Mondelli more than expected).
Fields of papers citing papers by Marco Mondelli
This network shows the impact of papers produced by Marco Mondelli. 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 Marco Mondelli. The network helps show where Marco Mondelli may publish in the future.
Co-authorship network of co-authors of Marco Mondelli
This figure shows the co-authorship network connecting the top 25 collaborators of Marco Mondelli. A scholar is included among the top collaborators of Marco Mondelli 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 Marco Mondelli. Marco Mondelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 16 | |
| 4 | 4 | |
| 5 | 0 | |
| 6 | Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks | 5 |
| 7 | 2 | |
| 8 | On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition | 7 |
| 9 | 18 | |
| 10 | 36 | |
| 11 | 15 | |
| 12 | Binary Linear Codes with Optimal Scaling and Quasi-Linear Complexity. | 2 |
| 13 | 17 | |
| 14 | Achieving the Superposition and Binning Regions for Broadcast Channels Using Polar Codes. | 2 |
| 15 | 10 | |
| 16 | 44 | |
| 17 | 8 | |
| 18 | 1 | |
| 19 | 6 | |
| 20 | 5 |
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.