Benoit Steiner
Impact in
- Computational Mathematics top 5%
- Tensor decomposition and applications
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
Papers in
-
- Advanced Neural Network Applications 2
-
- Advanced Electron Microscopy Techniques and Applications 1
- Co-authors
- Michaël Gharbi (1 shared paper)Andrew Adams (1 shared paper)Kayvon Fatahalian (1 shared paper)Tzu‐Mao Li (1 shared paper)Steven Johnson (1 shared paper)Frédo Durand (1 shared paper)Luke Anderson (1 shared paper)Riyadh Baghdadi (1 shared paper)
- Journals
- ACM Transactions on Graphics (1 paper)International Conference on Learning Representations (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Benoit Steiner
5 papers receiving 206 citations
Peers
Comparison fields: 5 of 30
- Computational Mathematics 23
- Hardware and Architecture 121
- Computer Vision and Pattern Recognition 105
- Computer Networks and Communications 61
- Artificial Intelligence 83
Countries citing papers authored by Benoit Steiner
This map shows the geographic impact of Benoit Steiner'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 Benoit Steiner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benoit Steiner more than expected).
Fields of papers citing papers by Benoit Steiner
This network shows the impact of papers produced by Benoit Steiner. 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 Benoit Steiner. The network helps show where Benoit Steiner may publish in the future.
Co-authors
The 19 scholars most cited alongside Benoit Steiner, 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 | 2019 | 129 | |
| 2 | A Hierarchical Model for Device Placement | 2018 | 55 |
| 3 | Value Learning for Throughput Optimization of Deep Learning Workloads | 2021 | 17 |
| 4 | Hierarchical Planning for Device Placement | 2018 | 9 |
| 5 | 2022 | 3 |
About Benoit Steiner
Benoit Steiner is a scholar working on Computer Vision and Pattern Recognition, Structural Biology, Information Systems, Information Systems and Management and Hardware and Architecture, having authored 5 papers that have together received 213 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (2 papers), Parallel Computing and Optimization Techniques (1 paper), Modular Robots and Swarm Intelligence (1 paper), Cloud Computing and Resource Management (1 paper), Scientific Computing and Data Management (1 paper), Neural Networks and Applications (1 paper), Advanced Electron Microscopy Techniques and Applications (1 paper) and Manufacturing Process and Optimization (1 paper). The work is most often cited by research in Computational Mathematics (23 citations), Hardware and Architecture (121 citations), Computer Vision and Pattern Recognition (105 citations), Computer Networks and Communications (61 citations) and Artificial Intelligence (83 citations). Benoit Steiner has collaborated with scholars based in United States and Israel. Frequent co-authors include Michaël Gharbi, Andrew Adams, Kayvon Fatahalian, Tzu‐Mao Li, Steven Johnson, Frédo Durand, Luke Anderson, Riyadh Baghdadi, Jonathan Ragan‐Kelley and Azalia Mirhoseini. Their work appears in journals such as ACM Transactions on Graphics 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.