Maurice Weiler
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Computational Mechanics
- Aerospace Engineering
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Martin StorathFred A. HamprechtMax WellingTaco CohenWouter BoomsmaMario GeigerPatrick ForréErik Verlinde
- Topics
- Advanced Neural Network Applications (2 papers)Neural Networks and Applications (1 paper)Mathematical Analysis and Transform Methods (1 paper)
- Cited by
- Computer Vision and Pattern RecognitionStructural BiologyComputer Graphics and Computer-Aided Design
- Journals
- UvA-DARE (University of Amsterdam)arXiv (Cornell University)WORLD SCIENTIFIC eBooks
- Partner nations
- NetherlandsUnited StatesDenmark
In The Last Decade
Maurice Weiler
7 papers receiving 253 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 158
- Artificial Intelligence 61
- Computational Mechanics 60
- Aerospace Engineering 28
- Radiology, Nuclear Medicine and Imaging 26
Countries citing papers authored by Maurice Weiler
This map shows the geographic impact of Maurice Weiler'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 Maurice Weiler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maurice Weiler more than expected).
Fields of papers citing papers by Maurice Weiler
This network shows the impact of papers produced by Maurice Weiler. 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 Maurice Weiler. The network helps show where Maurice Weiler may publish in the future.
Co-authorship network of co-authors of Maurice Weiler
This figure shows the co-authorship network connecting the top 25 collaborators of Maurice Weiler. A scholar is included among the top collaborators of Maurice Weiler based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maurice Weiler. Maurice Weiler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | A Wigner-Eckart Theorem for Group Equivariant Convolution Kernels | 1 |
| 3 | 1 | |
| 4 | 22 | |
| 5 | Gauge Equivariant Convolutional Networks and the Icosahedral CNN | 22 |
| 6 | 135 | |
| 7 | 3D steerable CNNs: learning rotationally equivariant features in volumetric data | 78 |
About Maurice Weiler
Maurice Weiler is a scholar working on Computer Vision and Pattern Recognition, Geology and Neurology, having authored 7 papers that have together received 261 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (2 papers), Neural Networks and Applications (1 paper) and Mathematical Analysis and Transform Methods (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (158 citations), Structural Biology (6 citations) and Computer Graphics and Computer-Aided Design (14 citations). Maurice Weiler has collaborated with scholars based in Netherlands, United States and Denmark. Frequent co-authors include Martin Storath, Fred A. Hamprecht, Max Welling, Taco Cohen, Wouter Boomsma, Mario Geiger, Patrick Forré, Erik Verlinde, Bradley Dice and Jes Frellsen. Their work appears in journals such as UvA-DARE (University of Amsterdam), arXiv (Cornell University) and WORLD SCIENTIFIC eBooks.
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.