James G. Scott
James G. Scott publishes mostly in Statistics and Probability, Artificial Intelligence and Modeling and Simulation, on topics such as Statistical Methods and Inference, Bayesian Methods and Mixture Models and Statistical Methods and Bayesian Inference.
- World rank
- #497,590 of 1,633,909 ranked researchers
- Rank in United States
- #165,791 of 358,040
- Works
- 27
- Citations
- 129
- Citations per work
- 4.8
What does James G. Scott research?
Shares of their own output, by the field each of their topics belongs to. The grey slice is everything not listed.
- 1Statistics and Probability42% of their works
- 2Artificial Intelligence25% of their works
- 3Modeling and Simulation3% of their works
- 4Public Health, Environmental and Occupational Health3% of their works
- 5Religious studies3% of their works
- 6Statistics, Probability and Uncertainty3% of their works
Research topics
- Statistical Methods and Inference
- Bayesian Methods and Mixture Models
- Statistical Methods and Bayesian Inference
- Advanced Statistical Methods and Models
- Statistical Distribution Estimation and Applications
- Neural Networks and Applications
- Advanced Graph Neural Networks
- Explainable Artificial Intelligence (XAI)
Which keywords describe James G. Scott's research?
The keywords of their largest research topics: Regularization, Variable Selection, Bayesian Inference, Bayesian Modeling, Clustering, Mixture Models, Multiple Imputation and Deep Learning.
- Self-Organizing Maps
- Machine Learning Interpretability
- Interpretable Models
- Skew Distributions
- Multicollinearity
- Deep Learning
- Mixture Models
- Bayesian Modeling
- Variable Selection
- Regularization
- Bayesian Inference
- Clustering
- Multiple Imputation
- Generalized Exponential
- Regression Analysis
- Graph Neural Networks
- Knowledge Graph Embedding
- Neural Networks
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most.
All 18 words, with their numbers
- Regularization71 topic
- Variable Selection71 topic
- Bayesian Inference52 topics
- Bayesian Modeling31 topic
- Clustering31 topic
- Mixture Models31 topic
- Multiple Imputation31 topic
- Deep Learning22 topics
- Generalized Exponential21 topic
- Multicollinearity21 topic
- Regression Analysis21 topic
- Skew Distributions21 topic
- Graph Neural Networks11 topic
- Interpretable Models11 topic
- Knowledge Graph Embedding11 topic
- Machine Learning Interpretability11 topic
- Neural Networks11 topic
- Self-Organizing Maps11 topic
Where does James G. Scott work?
James G. Scott's main affiliation in the publication record is The University of Texas at Austin, United States.
How many publications and citations does James G. Scott have?
Science Explorer counts 27 works and 129 citations for James G. Scott, ranking #497,590 of 1,633,909 researchers worldwide on the composite score.
Ranked on field-normalised excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Other researchers named James G. Scott
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