Jeff Calder
Jeff Calder publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Statistics and Probability, on topics such as Machine Learning and Algorithms, Statistical Methods and Inference and Domain Adaptation and Few-Shot Learning.
- World rank
- #1,812,094 of 7,710,434 ranked researchers
- Rank in United States
- #556,439 of 1,627,098
- Works
- 124
- Citations
- 909
- Citations per work
- 7.3
What does Jeff Calder research?
Jeff Calder's work is mostly in Computer Science (36%), Mathematics (15%), Medicine (5%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences6250.2%
- Computer Science4435.6%
- Mathematics1814.6%
- Everything else5644.9%
- Health Sciences64.9%
- Medicine64.9%
- 1Artificial Intelligence20% of their works
- 2Computer Vision and Pattern Recognition9% of their works
- 3Statistics and Probability9% of their works
- 4Computational Theory and Mathematics7% of their works
- 5Mathematical Physics6% of their works
- 6Radiology, Nuclear Medicine and Imaging5% of their works
Research topics
- Machine Learning and Algorithms
- Statistical Methods and Inference
- Domain Adaptation and Few-Shot Learning
- Advanced Graph Neural Networks
- Markov Chains and Monte Carlo Methods
- Forensic Anthropology and Bioarchaeology Studies
- Anomaly Detection Techniques and Applications
- Advanced Mathematical Modeling in Engineering
Which keywords describe Jeff Calder's research?
The keywords of their largest research topics: Semi-Supervised Learning, Deep Learning, Model Selection, High-Dimensional Data, Representation Learning, Active Learning, Machine Learning and Regularization.
- Multiscale Methods
- Anomaly Detection
- Markov Chain
- Graph Neural Networks
- Age Estimation
- Domain Adaptation
- Regularization
- Active Learning
- High-Dimensional Data
- Deep Learning
- Semi-Supervised Learning
- Model Selection
- Representation Learning
- Machine Learning
- Variable Selection
- Transfer Learning
- Bayesian Monte Carlo
- Knowledge Graph Embedding
- Sex Determination
- Heterogeneous
- Unsupervised
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 21 words, with their numbers
- Semi-Supervised Learning313 topics
- Deep Learning273 topics
- Model Selection202 topics
- High-Dimensional Data192 topics
- Representation Learning192 topics
- Active Learning121 topic
- Machine Learning121 topic
- Regularization121 topic
- Variable Selection121 topic
- Domain Adaptation111 topic
- Transfer Learning111 topic
- Age Estimation81 topic
- Bayesian Monte Carlo81 topic
- Graph Neural Networks81 topic
- Knowledge Graph Embedding81 topic
- Markov Chain81 topic
- Sex Determination81 topic
- Anomaly Detection71 topic
- Heterogeneous71 topic
- Multiscale Methods71 topic
- Unsupervised71 topic
Where does Jeff Calder work?
Jeff Calder's main affiliation in the publication record is University of Minnesota, United States.
How many publications and citations does Jeff Calder have?
OpenAlex counts 124 works and 909 citations for Jeff Calder, an h-index of 20, ranking #1,812,094 of 7,710,434 researchers worldwide on the quality 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.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
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