David Vigouroux
David Vigouroux publishes mostly in Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, on topics such as Explainable Artificial Intelligence (XAI), Adversarial Robustness in Machine Learning and Anomaly Detection Techniques and Applications.
- World rank
- #4,194,735 of 7,710,434 ranked researchers
- Rank in France
- #176,497 of 324,115
- Works
- 24
- Citations
- 188
- Citations per work
- 7.8
What does David Vigouroux research?
David Vigouroux's work is mostly in Computer Science (82%), Materials Science (3%), Decision Sciences (3%).
Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.
The fields and subfields, with their numbers
- Physical Sciences2085.4%
- Computer Science2082.2%
- Materials Science13.2%
- Everything else29.8%
- Social Sciences13.2%
- Decision Sciences13.2%
- Life Sciences01.6%
- 1Artificial Intelligence64% of their works
- 2Computer Vision and Pattern Recognition13% of their works
- 3Computational Theory and Mathematics5% of their works
- 4Information Systems and Management3% of their works
- 5Materials Chemistry3% of their works
- 6Biophysics2% of their works
Research topics
Which keywords describe David Vigouroux's research?
The keywords of their largest research topics: Deep Learning, Neural Networks, Machine Learning, Interpretable Models, Machine Learning Interpretability, Adversarial Examples, Robustness and Anomaly Detection.
- Stereo Vision
- Persistent Homology
- High-Throughput
- Backpropagation Learning
- Image Recognition
- Anomaly Detection
- Adversarial Examples
- Interpretable Models
- Neural Networks
- Deep Learning
- Machine Learning
- Machine Learning Interpretability
- Robustness
- Convolutional Neural Networks
- Unsupervised
- Depth Estimation
- Materials Informatics
- Self-Organizing Maps
- Topological Methods
Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.
All 19 words, with their numbers
- Deep Learning234 topics
- Neural Networks183 topics
- Machine Learning153 topics
- Interpretable Models121 topic
- Machine Learning Interpretability121 topic
- Adversarial Examples111 topic
- Robustness111 topic
- Anomaly Detection51 topic
- Convolutional Neural Networks51 topic
- Image Recognition51 topic
- Unsupervised51 topic
- Backpropagation Learning21 topic
- Depth Estimation21 topic
- High-Throughput21 topic
- Materials Informatics21 topic
- Persistent Homology21 topic
- Self-Organizing Maps21 topic
- Stereo Vision21 topic
- Topological Methods21 topic
Where does David Vigouroux work?
David Vigouroux's main affiliation in the publication record is IRT M2P, France.
How many publications and citations does David Vigouroux have?
OpenAlex counts 24 works and 188 citations for David Vigouroux, an h-index of 7, ranking #4,194,735 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.
Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.
Discussion
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