Diane Bouchacourt
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing
- Control and Systems Engineering
- Molecular Biology
- Co-authors
- Sebastian NowozinRyota TomiokaMarco BaroniDavid López-PazJonathan GordonBrenden M. LakeJacob Andreas
- Topics
- Natural Language Processing Techniques (3 papers)Speech and dialogue systems (2 papers)Generative Adversarial Networks and Image Synthesis (2 papers)
- Journals
- arXiv (Cornell University)Neural Information Processing SystemsDSpace@MIT (Massachusetts Institute of Technology)
- Partner nations
- United KingdomIsraelUnited States
In The Last Decade
Diane Bouchacourt
6 papers receiving 185 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 129
- Computer Vision and Pattern Recognition 107
- Signal Processing 16
- Control and Systems Engineering 14
- Molecular Biology 10
Countries citing papers authored by Diane Bouchacourt
This map shows the geographic impact of Diane Bouchacourt'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 Diane Bouchacourt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diane Bouchacourt more than expected).
Fields of papers citing papers by Diane Bouchacourt
This network shows the impact of papers produced by Diane Bouchacourt. 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 Diane Bouchacourt. The network helps show where Diane Bouchacourt may publish in the future.
Co-authorship network of co-authors of Diane Bouchacourt
This figure shows the co-authorship network connecting the top 25 collaborators of Diane Bouchacourt. A scholar is included among the top collaborators of Diane Bouchacourt 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 Diane Bouchacourt. Diane Bouchacourt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Permutation Equivariant Models for Compositional Generalization in Language | 28 |
| 2 | A Benchmark for Systematic Generalization in Grounded Language Understanding | 9 |
| 3 | 18 | |
| 4 | 85 | |
| 5 | 37 | |
| 6 | DISCO Nets : DISsimilarity COefficients Networks | 19 |
About Diane Bouchacourt
Diane Bouchacourt is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cultural Studies, having authored 6 papers that have together received 196 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (3 papers), Speech and dialogue systems (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (107 citations), Artificial Intelligence (129 citations) and Human-Computer Interaction (10 citations). Diane Bouchacourt has collaborated with scholars based in United Kingdom, Israel and United States. Frequent co-authors include Sebastian Nowozin, Ryota Tomioka, Marco Baroni, David López-Paz, Jonathan Gordon, Brenden M. Lake and Jacob Andreas. Their work appears in journals such as arXiv (Cornell University), Neural Information Processing Systems and DSpace@MIT (Massachusetts Institute of Technology).
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.