Marc Finzi
Impact in
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Advanced Image and Video Retrieval Techniques
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- Domain Adaptation and Few-Shot Learning
- Machine Learning and Data Classification
- Anomaly Detection Techniques and Applications
Papers in
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- Machine Learning and Data Classification 2
- Domain Adaptation and Few-Shot Learning 2
- Advanced Clustering Algorithms Research 1
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- Advanced Neural Network Applications 2
- Human Pose and Action Recognition 1
- Co-authors
- Pavel Izmailov (5 shared papers)Andrew Gordon Wilson (6 shared papers)Ben Athiwaratkun (2 shared papers)
- Journals
- Neural Information Processing Systems (1 paper)arXiv (Cornell University) (3 papers)
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
Marc Finzi
6 papers receiving 80 citations
Peers
Comparison fields: 5 of 27
- Computer Vision and Pattern Recognition 52
- Artificial Intelligence 63
- Radiology, Nuclear Medicine and Imaging 12
- Signal Processing 4
- Statistics and Probability 2
Countries citing papers authored by Marc Finzi
This map shows the geographic impact of Marc Finzi'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 Marc Finzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Finzi more than expected).
Fields of papers citing papers by Marc Finzi
This network shows the impact of papers produced by Marc Finzi. 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 Marc Finzi. The network helps show where Marc Finzi may publish in the future.
Co-authors
The 3 scholars most cited alongside Marc Finzi, 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 | 2018 | 56 | |
| 2 | Semi-Supervised Learning with Normalizing Flows | 2020 | 11 |
| 3 | Learning Invariances in Neural Networks from Training Data. | 2020 | 8 |
| 4 | Improving Consistency-Based Semi-Supervised Learning with Weight Averaging. | 2018 | 7 |
| 5 | 2021 | 1 | |
| 6 | Generalizing Convolutional Networks for Equivariance to Lie Groups on Arbitrary Continuous Data. | 2020 | 1 |
| 7 | 2023 | 0 |
About Marc Finzi
Marc Finzi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Geochemistry and Petrology and Signal Processing, having authored 7 papers that have together received 84 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (2 papers), Machine Learning and Data Classification (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Topological and Geometric Data Analysis (1 paper), Geological Modeling and Analysis (1 paper), Advanced Clustering Algorithms Research (1 paper), Music and Audio Processing (1 paper) and Human Pose and Action Recognition (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (52 citations), Artificial Intelligence (63 citations), Radiology, Nuclear Medicine and Imaging (12 citations), Signal Processing (4 citations) and Statistics and Probability (2 citations). Marc Finzi has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include Pavel Izmailov, Andrew Gordon Wilson and Ben Athiwaratkun. Their work appears in journals such as Neural Information Processing Systems and arXiv (Cornell University).
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.