Daniel Holtmann-Rice
About
In The Last Decade
Daniel Holtmann-Rice
16 papers receiving 166 citations
Peers
Comparison fields: 5 of 40
- Computer Vision and Pattern Recognition 75
- Artificial Intelligence 65
- Cognitive Neuroscience 61
- Atomic and Molecular Physics, and Optics 24
- Computational Mechanics 18
Countries citing papers authored by Daniel Holtmann-Rice
This map shows the geographic impact of Daniel Holtmann-Rice'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 Daniel Holtmann-Rice with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Holtmann-Rice more than expected).
Fields of papers citing papers by Daniel Holtmann-Rice
This network shows the impact of papers produced by Daniel Holtmann-Rice. 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 Daniel Holtmann-Rice. The network helps show where Daniel Holtmann-Rice may publish in the future.
Co-authorship network of co-authors of Daniel Holtmann-Rice
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Holtmann-Rice. A scholar is included among the top collaborators of Daniel Holtmann-Rice 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 Daniel Holtmann-Rice. Daniel Holtmann-Rice 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 | Breaking the Glass Ceiling for Embedding-Based Classifiers for Large Output Spaces | 15 |
| 3 | Loss Decomposition for Fast Learning in Large Output Spaces. | 3 |
| 4 | The Sparse Recovery Autoencoder. | 3 |
| 5 | 19 | |
| 6 | 9 | |
| 7 | 11 | |
| 8 | Multiscale Quantization for Fast Similarity Search | 27 |
| 9 | What's In A Patch, II: Visualizing generic surfaces. | 1 |
| 10 | 29 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 42 | |
| 15 | 3 | |
| 16 | 8 |
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.