Michael U. Gutmann
Impact in
- Artificial Intelligence top 1%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Gaussian Processes and Bayesian Inference
- Advanced Graph Neural Networks
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- Multimodal Machine Learning Applications
- Generative Adversarial Networks and Image Synthesis
Papers in
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- Markov Chains and Monte Carlo Methods 8
- Statistical Methods and Inference 6
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- Bayesian Methods and Mixture Models 10
- Gaussian Processes and Bayesian Inference 10
- Neural Networks and Applications 9
- Co-authors
- Aapo Hyvärinen (26 shared papers)Jukka Corander (13 shared papers)Jun-ichiro Hirayama (2 shared papers)Samuel Kaski (6 shared papers)Ritabrata Dutta (3 shared papers)Akash Kumar Srivastava (1 shared paper)Chris Russell (1 shared paper)Lazar Valkov (1 shared paper)
- Journals
- Bayesian Analysis (4 papers)Journal of Machine Learning Research (3 papers)Genetics (2 papers)Wellcome Open Research (2 papers)BMC Neuroscience (1 paper)
- Partner nations
- FinlandUnited KingdomJapan
In The Last Decade
Michael U. Gutmann
60 papers receiving 2.5k citations
Michael U. Gutmann's Hit Papers
Peers
Comparison fields: 5 of 168
- Artificial Intelligence 1.4k
- Computer Vision and Pattern Recognition 659
- Statistics and Probability 224
- Signal Processing 244
- Statistical and Nonlinear Physics 141
Countries citing papers authored by Michael U. Gutmann
This map shows the geographic impact of Michael U. Gutmann'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 U. Gutmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael U. Gutmann more than expected).
Fields of papers citing papers by Michael U. Gutmann
This network shows the impact of papers produced by Michael U. Gutmann. 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 U. Gutmann. The network helps show where Michael U. Gutmann may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael U. Gutmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Noise-contrastive estimation: A new estimation principle for unnormalized statistical models Hit paper breakdown → | 2010 | 738 |
| 2 | Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics Hit paper breakdown → | 2012 | 350 |
| 3 | 2020 | 166 | |
| 4 | 2016 | 136 | |
| 5 | VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning | 2017 | 135 |
| 6 | Proceedings of Conference on Uncertainty in Artificial Intelligence (UAI 2011) | 2011 | 132 |
| 7 | 2016 | 113 | |
| 8 | 2009 | 97 | |
| 9 | 2017 | 96 | |
| 10 | 2009 | 82 | |
| 11 | 1991 | 82 | |
| 12 | 2017 | 44 | |
| 13 | 2018 | 41 | |
| 14 | 2015 | 31 | |
| 15 | 2005 | 30 | |
| 16 | 2018 | 22 | |
| 17 | Adaptable Pouring: Teaching Robots Not to Spill using Fast but Approximate Fluid Simulation | 2017 | 18 |
| 18 | Proc. Conf. on Uncertainty in Artificial Intelligence (UAI) | 2010 | 18 |
| 19 | 2014 | 17 | |
| 20 | 2016 | 17 |
About Michael U. Gutmann
Michael U. Gutmann is a scholar working on Statistics and Probability, Artificial Intelligence, Signal Processing, Cognitive Neuroscience and Management Science and Operations Research, having authored 62 papers that have together received 2.6k indexed citations. Recurring topics across this work include Blind Source Separation Techniques (12 papers), Bayesian Methods and Mixture Models (10 papers), Gaussian Processes and Bayesian Inference (10 papers), Neural Networks and Applications (9 papers), Markov Chains and Monte Carlo Methods (8 papers), Neural dynamics and brain function (8 papers), Statistical Methods and Inference (6 papers) and Advanced Multi-Objective Optimization Algorithms (5 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Computer Vision and Pattern Recognition (659 citations), Statistics and Probability (224 citations), Signal Processing (244 citations) and Statistical and Nonlinear Physics (141 citations). Michael U. Gutmann has collaborated with scholars based in Finland, United Kingdom and Japan. Frequent co-authors include Aapo Hyvärinen, Jukka Corander, Jun-ichiro Hirayama, Samuel Kaski, Ritabrata Dutta, Akash Kumar Srivastava, Chris Russell, Lazar Valkov, Charles A. Sutton and William Paul Hanage. Their work appears in journals such as Bayesian Analysis, Journal of Machine Learning Research, Genetics, Wellcome Open Research and BMC Neuroscience.
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.