This map shows the geographic impact of Michael Wick'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 Michael Wick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Wick more than expected).
This network shows the impact of papers produced by Michael Wick. 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 Michael Wick. The network helps show where Michael Wick may publish in the future.
Co-authorship network of co-authors of Michael Wick
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Wick.
A scholar is included among the top collaborators of Michael Wick 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 Michael Wick. Michael Wick is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Wick, Michael, et al.. (2019). Unlocking Fairness: a Trade-off Revisited. Neural Information Processing Systems. 32. 8780–8789.21 indexed citations
4.
Wick, Michael, et al.. (2017). Enforcing Output Constraints via SGD: A Step Towards Neural Lagrangian Relaxation.. Neural Information Processing Systems.2 indexed citations
5.
Wick, Michael, et al.. (2017). Enforcing constraints on outputs with unconstrained inference.1 indexed citations
6.
Zaheer, Manzil, Jean-Baptiste Tristan, Michael Wick, & Guy L. Steele. (2017). Learning a Static Analyzer: A Case Study on a Toy Language.2 indexed citations
7.
Zaheer, Manzil, Michael Wick, Jean-Baptiste Tristan, Alexander J. Smola, & Guy L. Steele. (2016). Exponential Stochastic Cellular Automata for Massively Parallel Inference. International Conference on Artificial Intelligence and Statistics. 966–975.15 indexed citations
Wick, Michael, Sameer Singh, & Andrew McCallum. (2012). A Discriminative Hierarchical Model for Fast Coreference at Large Scale. Scholarworks (University of Massachusetts Amherst). 379–388.33 indexed citations
12.
Singh, Sameer, Michael Wick, & Andrew McCallum. (2012). Monte Carlo MCMC: Efficient Inference by Approximate Sampling. ScholarWorks@UMassAmherst (University of Massachusetts Amherst). 1104–1113.8 indexed citations
13.
Wick, Michael & Andrew McCallum. (2011). Query-Aware MCMC. Neural Information Processing Systems. 24. 2564–2572.14 indexed citations
14.
Day, David, Janet Hitzeman, Michael Wick, Keith Crouch, & Massimo Poesio. (2008). A Corpus for Cross-Document Co-reference.. Language Resources and Evaluation.6 indexed citations
15.
Wick, Michael, Khashayar Rohanimanesh, Andrew McCallum, & AnHai Doan. (2008). A Discriminative Approach to Ontology Mapping.. 16–19.3 indexed citations
16.
Rohanimanesh, Khashayar, Michael Wick, Sameer Singh, & Andrew McCallum. (2008). MAP inference in Large Factor Graphs with Reinforcement Learning. ScholarWorks@UMassAmherst (University of Massachusetts Amherst).2 indexed citations
McCallum, Andrew, Khashayar Rohanimanesh, Michael Wick, Karl Schultz, & Sameer Singh. (2008). FACTORIE: Efficient Probabilistic Programming for Relational Factor Graphs via Imperative Declarations of Structure, Inference and Learning. ScholarWorks@UMassAmherst (University of Massachusetts Amherst).11 indexed citations
19.
Culotta, Aron, Michael Wick, & Andrew McCallum. (2007). First-Order Probabilistic Models for Coreference Resolution. ScholarWorks@UMassAmherst (University of Massachusetts Amherst). 81–88.110 indexed citations
20.
Culotta, Aron, et al.. (2007). Author Disambiguation using Error-driven Machine Learning with a Ranking Loss Function. Scholarworks (University of Massachusetts Amherst).53 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.