Aurélien Bibaut
Aurélien Bibaut publishes mostly in Statistics and Probability, Artificial Intelligence and Management Science and Operations Research, on topics such as Statistical Methods and Inference, Advanced Causal Inference Techniques and Advanced Bandit Algorithms Research.
- World rank
- #3,029,254 of 7,710,434 ranked researchers
- Rank in United States
- #868,334 of 1,627,098
- Works
- 47
- Citations
- 553
- Citations per work
- 11.8
What does Aurélien Bibaut research?
Aurélien Bibaut's work is mostly in Mathematics (43%), Computer Science (27%), Decision Sciences (14%).
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 Sciences3472.3%
- Mathematics2042.9%
- Computer Science1327.0%
- Engineering12.4%
- Social Sciences816.7%
- Everything else511.0%
- 1Statistics and Probability40% of their works
- 2Artificial Intelligence27% of their works
- 3Management Science and Operations Research14% of their works
- 4Numerical Analysis2% of their works
- 5Finance2% of their works
- 6Control and Systems Engineering2% of their works
Research topics
Which keywords describe Aurélien Bibaut's research?
The keywords of their largest research topics: Bayesian Methods, Deep Learning, Regularization, Variable Selection, Causal Inference, Propensity Score, Bandit Optimization and Bayesian Optimization.
- Machine Learning Interpretability
- Robustness
- Robotics
- Semi-Supervised Learning
- Neural Networks
- Adaptive Designs
- Bayesian Optimization
- Propensity Score
- Variable Selection
- Deep Learning
- Bayesian Methods
- Regularization
- Causal Inference
- Bandit Optimization
- Machine Learning
- False Discovery Rate
- Active Learning
- Reinforcement Learning
- Adversarial Examples
- Interpretable Models
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 20 words, with their numbers
- Bayesian Methods302 topics
- Deep Learning193 topics
- Regularization181 topic
- Variable Selection181 topic
- Causal Inference161 topic
- Propensity Score161 topic
- Bandit Optimization151 topic
- Bayesian Optimization151 topic
- Machine Learning132 topics
- Adaptive Designs121 topic
- False Discovery Rate121 topic
- Neural Networks102 topics
- Active Learning91 topic
- Semi-Supervised Learning91 topic
- Reinforcement Learning61 topic
- Robotics61 topic
- Adversarial Examples41 topic
- Robustness41 topic
- Interpretable Models31 topic
- Machine Learning Interpretability31 topic
Where does Aurélien Bibaut work?
Aurélien Bibaut's main affiliation in the publication record is Netflix (United States), United States.
How many publications and citations does Aurélien Bibaut have?
OpenAlex counts 47 works and 553 citations for Aurélien Bibaut, an h-index of 8, ranking #3,029,254 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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