Christopher Burgess
About
In The Last Decade
Christopher Burgess
29 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 164
- Artificial Intelligence 700
- Computer Vision and Pattern Recognition 601
- General Health Professions 321
- Health 312
- Cognitive Neuroscience 215
Countries citing papers authored by Christopher Burgess
This map shows the geographic impact of Christopher Burgess'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 Christopher Burgess with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Burgess more than expected).
Fields of papers citing papers by Christopher Burgess
This network shows the impact of papers produced by Christopher Burgess. 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 Christopher Burgess. The network helps show where Christopher Burgess may publish in the future.
Co-authorship network of co-authors of Christopher Burgess
This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Burgess. A scholar is included among the top collaborators of Christopher Burgess 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 Christopher Burgess. Christopher Burgess 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 | 15 | |
| 3 | A Heuristic for Unsupervised Model Selection for Variational Disentangled Representation Learning. | 1 |
| 4 | Multi-Object Representation Learning with Iterative Variational Inference | 13 |
| 5 | 34 | |
| 6 | SCAN: Learning Hierarchical Compositional Visual Concepts | 17 |
| 7 | Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies | 18 |
| 8 | 8 | |
| 9 | beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework breakdown → | 1198 |
| 10 | 13 | |
| 11 | 30 | |
| 12 | 96 | |
| 13 | 11 | |
| 14 | 14 | |
| 15 | 16 | |
| 16 | 67 | |
| 17 | 41 | |
| 18 | A case for Indigenous natural resource management and health | 3 |
| 19 | 177 | |
| 20 | 9 |
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.