Maria M Robinson
Biographic Data
| ID | 1901921 |
|---|---|
| NAME | Maria M Robinson |
| GIVEN NAMES | Maria M |
| FAMILY NAME | Robinson |
| SIGNATURE | ROBINSON M M |
| AFFILIATIONS | University of California San Diego |
| ORCID | 0000-0002-9797-4068 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
The Target Confusability Competition ensemble model predicts full feature distribution reports
Zooming in on what counts as core and auxiliary
Research on best practices in theory assessment highlights that testing theories is challenging because they inherit a new set of assumptions as soon as they are linked to a specific methodology. In this article, we integrate and build on this work by demonstrating the breadth of these challenges. We show that tracking auxiliary assumptions is difficult because they are made at different stages of theory testing and at multiple levels of a theory…
Measuring memory is harder than you think
A quantitative model of ensemble perception as summed activation in feature space
Ensemble perception is a process by which we summarize complex scenes. Despite the importance of ensemble perception to everyday cognition, there are few computational models that provide a formal account of this process. Here we develop and test a model in which ensemble representations reflect the global sum of activation signals across all individual items. We leverage this set of minimal assumptions to formally connect a model of memory for i…
Amplification in the evaluation of multiple emotional expressions over time
Is there a K in capacity? Assessing the structure of visual short-term memory
No prominent works on this page.
Is there a K in capacity? Assessing the structure of visual short-term memory
Amplification in the evaluation of multiple emotional expressions over time
Measuring memory is harder than you think
A quantitative model of ensemble perception as summed activation in feature space
Ensemble perception is a process by which we summarize complex scenes. Despite the importance of ensemble perception to everyday cognition, there are few computational models that provide a formal account of this process. Here we develop and test a model in which ensemble representations reflect the global sum of activation signals across all individual items. We leverage this set of minimal assumptions to formally connect a model of memory for i…
Zooming in on what counts as core and auxiliary
Research on best practices in theory assessment highlights that testing theories is challenging because they inherit a new set of assumptions as soon as they are linked to a specific methodology. In this article, we integrate and build on this work by demonstrating the breadth of these challenges. We show that tracking auxiliary assumptions is difficult because they are made at different stages of theory testing and at multiple levels of a theory…
The Target Confusability Competition ensemble model predicts full feature distribution reports
Cognitive psychology (4 works) · Psychology (4 works) · Cognition (3 works) · Cognitive science (3 works) · Computer Science (3 works) · Memory Processes and Influences (3 works) · Neural and Behavioral Psychology Studies (3 works) · Working memory (3 works) · Artificial Intelligence (2 works) · Perception (2 works)