Gregory Z. Grudić

772 citations
36 papers · 549 indexed · h-index 13

Gregory Z. Grudić

31 papers receiving 514 citations

Peers

Gregory Z. Grudić
Comparison fields: 5 of 103
  • Surgery 146
  • Artificial Intelligence 138
  • Computer Vision and Pattern Recognition 123
  • Emergency Medicine 116
  • Biomedical Engineering 103
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Countries citing papers authored by Gregory Z. Grudić

Since Specialization
Citations

This map shows the geographic impact of Gregory Z. Grudić'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 Gregory Z. Grudić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregory Z. Grudić more than expected).

Fields of papers citing papers by Gregory Z. Grudić

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregory Z. Grudić. 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 Gregory Z. Grudić. The network helps show where Gregory Z. Grudić may publish in the future.

Co-authorship network of co-authors of Gregory Z. Grudić

This figure shows the co-authorship network connecting the top 25 collaborators of Gregory Z. Grudić. A scholar is included among the top collaborators of Gregory Z. Grudić 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 Gregory Z. Grudić. Gregory Z. Grudić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 10
2 17
3 67
4 17
5 29
6 0
7 0
8
Mixture of Watson Distributions: A Generative Model for Hyperspherical Embeddings
15
9 14
10
An experimental analysis of classifier ensembles for learning drifting concepts over time in autonomous outdoor robot navigation
10
11 7
12 15
13
Unsupervised Outlier Detection and Semi-Supervised Learning ; CU-CS-976-04
8
14
Sparse Greedy Minimax Probability Machine Classification
7
15
A Formulation for Minimax Probability Machine Regression
60
16 19
17
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
1
18
Localizing Search in Reinforcement Learning
8
19
Localizing Policy Gradient Estimates to Action Transition
8
20
Is nonparametric learning practical in very high dimensional spaces
4

About Gregory Z. Grudić

Gregory Z. Grudić is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Emergency Medicine, having authored 36 papers that have together received 549 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (7 papers), Robotic Path Planning Algorithms (6 papers) and Neural Networks and Applications (6 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (68 citations), Emergency Medicine (116 citations) and Computer Vision and Pattern Recognition (123 citations). Gregory Z. Grudić has collaborated with scholars based in United States and Canada. Frequent co-authors include Víctor A. Convertino, P.D. Lawrence, Steven L. Moulton, Carmen Hinojosa‐Laborde, Jane Mulligan, Lyle Ungar, Caroline A. Rickards, Robert T. Gerhardt, Lorne H. Blackbourne and Kathy L. Ryan. Their work appears in journals such as IEEE Transactions on Robotics and Automation, Journal of Vision and Shock.

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.

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