François Deheeger
François Deheeger publishes mostly in Artificial Intelligence, Statistics, Probability and Uncertainty and Civil and Structural Engineering, on topics such as Probabilistic and Robust Engineering Design, Domain Adaptation and Few-Shot Learning and Anomaly Detection Techniques and Applications.
- World rank
- #3,061,853 of 7,710,434 ranked researchers
- Rank in France
- #129,659 of 324,115
- Works
- 18
- Citations
- 1.1k
- Citations per work
- 58.7
What does François Deheeger research?
François Deheeger's work is mostly in Computer Science (39%), Engineering (16%), Decision Sciences (12%).
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 Sciences1163.3%
- Computer Science738.8%
- Engineering316.3%
- Mathematics18.2%
- Everything else424.5%
- Social Sciences212.2%
- Decision Sciences212.2%
- 1Artificial Intelligence33% of their works
- 2Statistics, Probability and Uncertainty12% of their works
- 3Civil and Structural Engineering10% of their works
- 4Statistics and Probability8% of their works
- 5Computational Theory and Mathematics6% of their works
- 6Mechanical Engineering6% of their works
Research topics
- Probabilistic and Robust Engineering Design
- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
- Advanced Multi-Objective Optimization Algorithms
- Structural Health Monitoring Techniques
- Adversarial Robustness in Machine Learning
- Machine Learning and Data Classification
- Machine Learning and Algorithms
Which keywords describe François Deheeger's research?
The keywords of their largest research topics: Deep Learning, Meta-Learning, Semi-Supervised Learning, Sensitivity Analysis, Uncertainty Quantification, Neural Networks, Domain Adaptation and Machine Learning.
- Noisy Labels
- Gaussian Processes
- Active Learning
- Vibration-based Damage Identification
- Multiobjective Optimization
- Anomaly Detection
- Machine Learning
- Neural Networks
- Sensitivity Analysis
- Meta-Learning
- Deep Learning
- Semi-Supervised Learning
- Uncertainty Quantification
- Domain Adaptation
- Transfer Learning
- Evolutionary Algorithms
- Unsupervised
- Wireless Sensors
- Adversarial Examples
- Hyperparameter Optimization
- Robustness
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.
All 21 words, with their numbers
- Deep Learning73 topics
- Meta-Learning62 topics
- Semi-Supervised Learning62 topics
- Sensitivity Analysis61 topic
- Uncertainty Quantification61 topic
- Neural Networks52 topics
- Domain Adaptation41 topic
- Machine Learning42 topics
- Transfer Learning41 topic
- Anomaly Detection31 topic
- Evolutionary Algorithms31 topic
- Multiobjective Optimization31 topic
- Unsupervised31 topic
- Vibration-based Damage Identification31 topic
- Wireless Sensors31 topic
- Active Learning21 topic
- Adversarial Examples21 topic
- Gaussian Processes21 topic
- Hyperparameter Optimization21 topic
- Noisy Labels21 topic
- Robustness21 topic
Where does François Deheeger work?
François Deheeger's main affiliation in the publication record is Michelin (France), France.
How many publications and citations does François Deheeger have?
OpenAlex counts 18 works and 1,056 citations for François Deheeger, an h-index of 6, ranking #3,061,853 of 7,710,434 researchers worldwide on the quality score.
Ranked on field-normalised 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.
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