Carlos Scheidegger
About
In The Last Decade
Carlos Scheidegger
77 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Computer Vision and Pattern Recognition 1.2k
- Artificial Intelligence 1.1k
- Information Systems and Management 741
- Safety Research 676
- Computer Networks and Communications 622
Countries citing papers authored by Carlos Scheidegger
This map shows the geographic impact of Carlos Scheidegger'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 Carlos Scheidegger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlos Scheidegger more than expected).
Fields of papers citing papers by Carlos Scheidegger
This network shows the impact of papers produced by Carlos Scheidegger. 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 Carlos Scheidegger. The network helps show where Carlos Scheidegger may publish in the future.
Co-authorship network of co-authors of Carlos Scheidegger
This figure shows the co-authorship network connecting the top 25 collaborators of Carlos Scheidegger. A scholar is included among the top collaborators of Carlos Scheidegger 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 Carlos Scheidegger. Carlos Scheidegger 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 | 41 | |
| 3 | Shapley Residuals: Quantifying the limits of the Shapley value for explanations | 19 |
| 4 | Disentangling Influence: Using disentangled representations to audit model predictions | 2 |
| 5 | NNCubes: Learned Structures for Visual Data Exploration. | 3 |
| 6 | Decision making with limited feedback:Error bounds for predictive policing and recidivism prediction | 5 |
| 7 | Persistent Homology Guided Exploration of Time-Varying Graphs. | 1 |
| 8 | Hiring by Algorithm: Predicting and Preventing Disparate Impact | 18 |
| 9 | Certifying and Removing Disparate Impact breakdown → | 838 |
| 10 | 182 | |
| 11 | 21 | |
| 12 | Edge Flows: Stratified Morse Theory for Simple, Correct Isosurface Extraction | 1 |
| 13 | 13 | |
| 14 | 18 | |
| 15 | 45 | |
| 16 | 37 | |
| 17 | 9 | |
| 18 | 62 | |
| 19 | 58 | |
| 20 | Computation on GPUs: from a programmable pipeline to an efficient stream processor | 6 |
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.