Chinmay Hegde
About
In The Last Decade
Chinmay Hegde
94 papers receiving 934 citations
Peers
Comparison fields: 5 of 93
- Computational Mechanics 388
- Computer Vision and Pattern Recognition 344
- Artificial Intelligence 221
- Biomedical Engineering 164
- Signal Processing 152
Countries citing papers authored by Chinmay Hegde
This map shows the geographic impact of Chinmay Hegde'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 Chinmay Hegde with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chinmay Hegde more than expected).
Fields of papers citing papers by Chinmay Hegde
This network shows the impact of papers produced by Chinmay Hegde. 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 Chinmay Hegde. The network helps show where Chinmay Hegde may publish in the future.
Co-authorship network of co-authors of Chinmay Hegde
This figure shows the co-authorship network connecting the top 25 collaborators of Chinmay Hegde. A scholar is included among the top collaborators of Chinmay Hegde 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 Chinmay Hegde. Chinmay Hegde 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 | 3 | |
| 3 | 9 | |
| 4 | 21 | |
| 5 | 1 | |
| 6 | 10 | |
| 7 | 7 | |
| 8 | 23 | |
| 9 | Attribute-Controlled Traffic Data Augmentation Using Conditional Generative Models | 4 |
| 10 | Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors | 5 |
| 11 | On the Dynamics of Gradient Descent for Autoencoders | 5 |
| 12 | Provably Accurate Double-Sparse Coding | 1 |
| 13 | 24 | |
| 14 | Towards provable learning of polynomial neural networks using low-rank matrix estimation | 6 |
| 15 | Fast, Sample-Efficient Algorithms for Structured Phase Retrieval | 20 |
| 16 | Phase Retrieval Using Structured Sparsity: A Sample Efficient Algorithmic Framework. | 3 |
| 17 | Fast recovery from a union of subspaces | 6 |
| 18 | Fast Algorithms for Structured Sparsity | 10 |
| 19 | High-dimensional data fusion via joint manifold learning | 5 |
| 20 | Random Projections for Manifold Learning | 69 |
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.