Christopher J. Merz

3.2k total citations · 1 hit paper
10 papers, 1.9k citations indexed

About

Christopher J. Merz is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Christopher J. Merz has authored 10 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 3 papers in Information Systems and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Christopher J. Merz's work include Neural Networks and Applications (7 papers), Machine Learning and Algorithms (2 papers) and Face and Expression Recognition (2 papers). Christopher J. Merz is often cited by papers focused on Neural Networks and Applications (7 papers), Machine Learning and Algorithms (2 papers) and Face and Expression Recognition (2 papers). Christopher J. Merz collaborates with scholars based in United States and Russia. Christopher J. Merz's co-authors include Michael J. Pazzani, Stephen Aylward and Andrea Danyluk and has published in prestigious journals such as Machine Learning, IEEE Expert and Neural Information Processing Systems.

In The Last Decade

Christopher J. Merz

9 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

UCI Repository of Machine Learning Databases

1996 1.6k citations Christopher J. Merz Medical Entomology and Zoology profile →

Peers

Christopher J. Merz

AI

CVPR

IS

CTM

SP

Patrick M. Murphy United States

Stephen D. Bay United States

Geoffrey G. Towell United States

José Otero Spain

Shuyin Xia China

Ayhan Demiriz Türkiye

Dietrich Wettschereck United States

M.H.C. Law United States

Qinbao Song China

Patrick M. Murphy United States

Christopher J. Merz

1.1k ×0.7

AI

448 ×0.9

CVPR

335 ×0.7

IS

252 ×0.8

CTM

149 ×0.6

SP

Citations per year, relative to Christopher J. Merz Christopher J. Merz (= 1×) peers Patrick M. Murphy

Countries citing papers authored by Christopher J. Merz

Since Specialization

Citations

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

Fields of papers citing papers by Christopher J. Merz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher J. Merz. 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 Christopher J. Merz. The network helps show where Christopher J. Merz may publish in the future.

Co-authorship network of co-authors of Christopher J. Merz

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Merz, Christopher J., et al.. (2003). SeMi-supervised adaptive resonance theory (SMART2). 3. 851–856. 20 indexed citations

2.

Merz, Christopher J. & Michael J. Pazzani. (2002). Parameter tuning for the MAX expert system. 3. 632–639.

3.

Merz, Christopher J.. (1999). Using Correspondence Analysis to Combine Classifiers. Machine Learning. 36(1-2). 33–58. 134 indexed citations

4.

Merz, Christopher J. & Michael J. Pazzani. (1999). A Principal Components Approach to Combining Regression Estimates. Machine Learning. 36(1-2). 9–32. 77 indexed citations

5.

Merz, Christopher J. & Michael J. Pazzani. (1998). Classification and regression by combining models. 31 indexed citations

6.

Merz, Christopher J.. (1997). Combining Classifiers Using Correspondence Analysis. Neural Information Processing Systems. 10. 591–597. 12 indexed citations

7.

Merz, Christopher J. & Michael J. Pazzani. (1996). Combining Neural Network Regression Estimates with Regularized Linear Weights. Neural Information Processing Systems. 9. 564–570. 32 indexed citations

8.

Merz, Christopher J.. (1996). UCI Repository of Machine Learning Databases. Medical Entomology and Zoology. 1582 indexed citations breakdown →

9.

Merz, Christopher J., Michael J. Pazzani, & Andrea Danyluk. (1996). Tuning numeric parameters to troubleshoot a telephone-network loop. IEEE Expert. 11(1). 44–49. 1 indexed citations

10.

Merz, Christopher J., et al.. (1992). Neural network analysis of nondestructive evaluation patterns. 643–650. 6 indexed citations

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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