Daniel Kifer
About
In The Last Decade
Daniel Kifer
94 papers receiving 7.1k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Artificial Intelligence 6.1k
- Sociology and Political Science 2.8k
- Computer Science Applications 996
- Information Systems 947
- Computer Vision and Pattern Recognition 590
Countries citing papers authored by Daniel Kifer
This map shows the geographic impact of Daniel Kifer'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 Kifer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Kifer more than expected).
Fields of papers citing papers by Daniel Kifer
This network shows the impact of papers produced by Daniel Kifer. 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 Kifer. The network helps show where Daniel Kifer may publish in the future.
Co-authorship network of co-authors of Daniel Kifer
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Kifer. A scholar is included among the top collaborators of Daniel Kifer 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 Kifer. Daniel Kifer 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 | 1 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 15 | |
| 9 | 86 | |
| 10 | 13 | |
| 11 | 66 | |
| 12 | Cloud-based interactive database management suite integrated with deep learning-based annotation tool for landslide mapping | 2 |
| 13 | Deep learning of the precursory signatures in active source seismic data for improved prediction of laboratory earthquake | 1 |
| 14 | A physics-informed deep learning method for prediction of CO2 storage site response | 1 |
| 15 | A New Class of Private Chi-Square Hypothesis Tests. | 13 |
| 16 | A New Class of Private Chi-Square Tests | 2 |
| 17 | Private Convex Optimization for Empirical Risk Minimization with Applications to High-dimensional Regression. | 23 |
| 18 | Private Convex Empirical Risk Minimization and High-dimensional Regression | 75 |
| 19 | L-diversity: privacy beyond k-anonymity breakdown → | 1495 |
| 20 | A Vision for PetaByte Data Management and Analyis Services for the Arecibo Telescope. | 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.