Mark A. Pitt
About
In The Last Decade
Mark A. Pitt
145 papers receiving 4.9k citations
Peers
Comparison fields: 5 of 196
- Cognitive Neuroscience 2.0k
- Experimental and Cognitive Psychology 1.9k
- Artificial Intelligence 1.5k
- Developmental and Educational Psychology 915
- Signal Processing 478
Countries citing papers authored by Mark A. Pitt
This map shows the geographic impact of Mark A. Pitt'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 Mark A. Pitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark A. Pitt more than expected).
Fields of papers citing papers by Mark A. Pitt
This network shows the impact of papers produced by Mark A. Pitt. 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 Mark A. Pitt. The network helps show where Mark A. Pitt may publish in the future.
Co-authorship network of co-authors of Mark A. Pitt
This figure shows the co-authorship network connecting the top 25 collaborators of Mark A. Pitt. A scholar is included among the top collaborators of Mark A. Pitt 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 Mark A. Pitt. Mark A. Pitt 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 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | Context variability promotes generalization in reading aloud: Insight from a neural network simulation. | 1 |
| 9 | The Scaled Target Learning Model: A Novel Computational Model of the Balloon Analogue Risk Task. | 1 |
| 10 | Modeling Delay Discounting using Gaussian Process with Active Learning. | 1 |
| 11 | Active Learning for a Number-Line Task with Two Design Variables. | 1 |
| 12 | 11 | |
| 13 | Rate-dependent speech processing can be speech-specific: Evidence from the disappearance of words under changes in context speech rate. | 1 |
| 14 | 5 | |
| 15 | Cognitive Modeling Repository | 6 |
| 16 | Better data with fewer participants and trials: improving experiment efficiency with adaptive design optimization | 4 |
| 17 | Advances in Minimum Description Length: Theory and Applications | 276 |
| 18 | Advances in Minimum Description Length: Theory and Applications (Neural Information Processing) | 18 |
| 19 | An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science | 6 |
| 20 | Global Model Analysis by Landscaping | 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.