Matthew Johnson

3.5k citations
52 papers · 1.4k indexed · h-index 17

Impact in

Papers in

    • Human-Automation Interaction and Safety 13
    • Bayesian Methods and Mixture Models 5
    • Multi-Agent Systems and Negotiation 5
    • Gaussian Processes and Bayesian Inference 4

Matthew Johnson

51 papers receiving 1.3k citations

Peers

Matthew Johnson
Comparison fields: 5 of 135
  • Social Psychology 381
  • Artificial Intelligence 501
  • Management Information Systems 119
  • Radiological and Ultrasound Technology 64
  • Health Informatics 16
Replace Jacob W. Crandall with:
Jacob W. Crandall United States
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W. Bradley Knox United States
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Citations per field
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Citations per year

Countries citing papers authored by Matthew Johnson

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Johnson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Johnson. 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 Matthew Johnson. The network helps show where Matthew Johnson may publish in the future.

Co-authors

The 25 scholars most cited alongside Matthew Johnson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew Johnson Line = papers co-authored together Matthew Johnson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20232
2
Learning Differential Equations that are Easy to Solve
20204
3
Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models
20182
4
Composing graphical models with neural networks for structured representations and fast inference
201658
5 20166
6
Structured VAEs: Composing Probabilistic Graphical Models and Variational Autoencoders
20168
7
Cross-corpora unsupervised learning of trajectories in autism spectrum disorders
20163
8 201621
9 201519
10 20156
11
Stochastic Variational Inference for Bayesian Time Series Models
201437
12 20119
13 201144
14 20105
15 20102
16 200847
17 20081
18 20083
19
Visuo-Cognitive Perspective Taking for Action Recognition
20072
20 1996141

About Matthew Johnson

Matthew Johnson is a scholar working on Social Psychology, Artificial Intelligence, Communication, Human-Computer Interaction and Control and Systems Engineering, having authored 52 papers that have together received 1.4k indexed citations. Recurring topics across this work include Human-Automation Interaction and Safety (13 papers), Bayesian Methods and Mixture Models (5 papers), Multi-Agent Systems and Negotiation (5 papers), Systems Engineering Methodologies and Applications (5 papers), Service-Oriented Architecture and Web Services (5 papers), Disaster Management and Resilience (4 papers), Public Relations and Crisis Communication (4 papers) and Gaussian Processes and Bayesian Inference (4 papers). The work is most often cited by research in Social Psychology (381 citations), Artificial Intelligence (501 citations), Management Information Systems (119 citations), Radiological and Ultrasound Technology (64 citations) and Health Informatics (16 citations). Matthew Johnson has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Jeffrey M. Bradshaw, Paul J. Feltovich, Robert R. Hoffman, Alonso Vera, Maarten Sierhuis, Catholijn M. Jonker, M. Birna van Riemsdijk, David D. Woods, Ryan P. Adams and Alexander B. Wiltschko. Their work appears in journals such as IEEE Intelligent Systems, Bulletin of the Atomic Scientists, Nature Neuroscience, ACM Transactions on Intelligent Systems and Technology and Journal of Management Information Systems.

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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