Matt Hoffman
Impact in
- Signal Processing top 5%
- Music and Audio Processing
- Speech and Audio Processing
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- Music Technology and Sound Studies
Papers in
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- Gaussian Processes and Bayesian Inference 4
- Bayesian Methods and Mixture Models 3
- Machine Learning and Algorithms 2
- Domain Adaptation and Few-Shot Learning 1
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- Music Technology and Sound Studies 4
- Co-authors
- David M. Blei (2 shared papers)David Mimno (1 shared paper)Noam Shazeer (1 shared paper)Ashish Vaswani (1 shared paper)Jakob Uszkoreit (1 shared paper)Ian Simon (1 shared paper)Cheng-Zhi Anna Huang (1 shared paper)Monica Dinculescu (1 shared paper)
- Journals
- International Journal of Sports Science & Coaching (1 paper)Journal of the Association for Information Systems (1 paper)Lecture notes in computer science (1 paper)SMARTech Repository (Georgia Institute of Technology) (1 paper)International Conference on Learning Representations (1 paper)
- Partner nations
- United StatesCanadaAustralia
In The Last Decade
Matt Hoffman
14 papers receiving 282 citations
Peers
Comparison fields: 5 of 56
- Signal Processing 155
- Computer Vision and Pattern Recognition 138
- Artificial Intelligence 140
- Cognitive Neuroscience 65
- Computational Mathematics 2
Countries citing papers authored by Matt Hoffman
This map shows the geographic impact of Matt Hoffman'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 Matt Hoffman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matt Hoffman more than expected).
Fields of papers citing papers by Matt Hoffman
This network shows the impact of papers produced by Matt Hoffman. 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 Matt Hoffman. The network helps show where Matt Hoffman may publish in the future.
Co-authors
The 25 scholars most cited alongside Matt Hoffman, 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 | Music Transformer: Generating Music with Long-Term Structure | 2019 | 146 |
| 2 | Sparse stochastic inference for latent Dirichlet allocation | 2012 | 51 |
| 3 | 2016 | 40 | |
| 4 | 2012 | 19 | |
| 5 | New inference strategies for solving Markov decision processes using reversible jump MCMC | 2009 | 18 |
| 6 | 2015 | 9 | |
| 7 | Trans-dimensional MCMC for Bayesian policy learning | 2007 | 8 |
| 8 | 2019 | 6 | |
| 9 | Scalable nonparametric Bayesian multilevel clustering | 2016 | 3 |
| 10 | 2021 | 3 | |
| 11 | 2009 | 3 | |
| 12 | Feature-Based Synthesis for Sonification and Psychoacoustic Research | 2006 | 2 |
| 13 | 2007 | 1 | |
| 14 | 2007 | 1 |
About Matt Hoffman
Matt Hoffman is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Statistics and Probability and Control and Systems Engineering, having authored 14 papers that have together received 310 indexed citations. Recurring topics across this work include Music and Audio Processing (4 papers), Music Technology and Sound Studies (4 papers), Gaussian Processes and Bayesian Inference (4 papers), Bayesian Methods and Mixture Models (3 papers), Speech and Audio Processing (3 papers), Markov Chains and Monte Carlo Methods (2 papers), Machine Learning and Algorithms (2 papers) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Signal Processing (155 citations), Computer Vision and Pattern Recognition (138 citations), Artificial Intelligence (140 citations), Cognitive Neuroscience (65 citations) and Computational Mathematics (2 citations). Matt Hoffman has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include David M. Blei, David Mimno, Noam Shazeer, Ashish Vaswani, Jakob Uszkoreit, Ian Simon, Cheng-Zhi Anna Huang, Monica Dinculescu, Curtis Hawthorne and Douglas Eck. Their work appears in journals such as International Journal of Sports Science & Coaching, Journal of the Association for Information Systems, Lecture notes in computer science, SMARTech Repository (Georgia Institute of Technology) and International Conference on Learning Representations.
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.