William T. Freeman
-
- Human Pose and Action Recognition 2
- Human-Computer Interaction top 2%
- Signal Processing top 5%
- Time Series Analysis and Forecasting 2
- Music and Audio Processing 2
- Artificial Intelligence top 2%
- Bayesian Modeling and Causal Inference 4
- Machine Learning and ELM 2
-
- Error Correcting Code Techniques 3
- Distributed Sensor Networks and Detection Algorithms 2
-
- Educational Games and Gamification 2
- Co-authors
- Yair WeissJonathan S. YedidiaFrédo DurandMichael RubinsteinJohn V. GuttagEugene ShihHaoyu WuJoshua B. Tenenbaum
- Partner nations
- United StatesJapanGermany
In The Last Decade
William T. Freeman
19 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Computer Vision and Pattern Recognition 867
- Human-Computer Interaction 155
- Signal Processing 233
- Artificial Intelligence 690
- Computer Networks and Communications 363
Countries citing papers authored by William T. Freeman
This map shows the geographic impact of William T. Freeman'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 William T. Freeman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William T. Freeman more than expected).
Fields of papers citing papers by William T. Freeman
This network shows the impact of papers produced by William T. Freeman. 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 William T. Freeman. The network helps show where William T. Freeman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside William T. Freeman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2021 | 26 | |
| 4 | A Comparative Evaluation of Approximate Probabilistic Simulation and Deep Neural Networks as Accounts of Human Physical Scene Understanding | 2016 | 1 |
| 5 | 2016 | 56 | |
| 6 | 2013 | 5 | |
| 7 | 2012 | 13 | |
| 8 | 2012 | 174 | |
| 9 | Eulerian video magnification for revealing subtle changes in the worldbreakdown → | 2012 | 905 |
| 10 | 2008 | 131 | |
| 11 | Nonparametric Belief Propagation and Facial Appearance Estimation | 2002 | 5 |
| 12 | Bethe free energy, Kikuchi approximations, and belief propagation algorithms | 2001 | 95 |
| 13 | 2001 | 363 | |
| 14 | 2001 | 7 | |
| 15 | Generalized Belief Propagationbreakdown → | 2000 | 558 |
| 16 | Loopy Belief Propagation Gives Exact Posterior Means for Gaussian | 1999 | 1 |
| 17 | Separating Style and Content | 1996 | 72 |
| 18 | 1994 | 22 | |
| 19 | 1994 | 11 | |
| 20 | Suggestions regarding certain representations in ALGOL 68 | 1972 | 1 |
About William T. Freeman
William T. Freeman is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 21 papers that have together received 2.6k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (4 papers), Error Correcting Code Techniques (3 papers), Machine Learning and ELM (2 papers), Time Series Analysis and Forecasting (2 papers), Human Pose and Action Recognition (2 papers), Distributed Sensor Networks and Detection Algorithms (2 papers), Music and Audio Processing (2 papers) and Educational Games and Gamification (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (867 citations), Human-Computer Interaction (155 citations) and Signal Processing (233 citations). William T. Freeman has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include Yair Weiss, Jonathan S. Yedidia, Frédo Durand, Michael Rubinstein, John V. Guttag, Eugene Shih, Haoyu Wu, Joshua B. Tenenbaum, Edward H. Adelson and Haoyu Wu. Their work appears in journals such as ACM Transactions on Graphics, Computer, Neural Computation, IEEE Computer Graphics and Applications and IEEE Multimedia.
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.