Felix Dangel
Felix Dangel publishes mostly in Artificial Intelligence, Statistical and Nonlinear Physics and Atomic and Molecular Physics, and Optics, on topics such as Model Reduction and Neural Networks, Stochastic Gradient Optimization Techniques and Neural Networks and Applications.
- World rank
- #4,082,359 of 7,710,434 ranked researchers
- Rank in Canada
- #126,298 of 183,316
- Works
- 37
- Citations
- 149
- Citations per work
- 4.0
What does Felix Dangel research?
Felix Dangel's work is mostly in Computer Science (48%), Physics and Astronomy (20%), Engineering (5%).
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 Sciences2772.3%
- Computer Science1847.5%
- Physics and Astronomy719.8%
- Engineering25.0%
- Everything else1027.7%
- 1Artificial Intelligence36% of their works
- 2Statistical and Nonlinear Physics13% of their works
- 3Atomic and Molecular Physics, and Optics7% of their works
- 4Computer Vision and Pattern Recognition7% of their works
- 5Computational Theory and Mathematics5% of their works
- 6Computational Mechanics5% of their works
Research topics
- Model Reduction and Neural Networks
- Stochastic Gradient Optimization Techniques
- Neural Networks and Applications
- Domain Adaptation and Few-Shot Learning
- Parallel Computing and Optimization Techniques
- Tensor decomposition and applications
- Adversarial Robustness in Machine Learning
- Gaussian Processes and Bayesian Inference
Which keywords describe Felix Dangel's research?
The keywords of their largest research topics: Deep Learning, Machine Learning, Neural Networks, Model Reduction, Partial Differential Equations, Random Projections, Stochastic Gradient Descent and Backpropagation Learning.
- Robustness
- Adversarial Examples
- Performance Optimization
- Multilinear Algebra
- Domain Adaptation
- Backpropagation Learning
- Random Projections
- Model Reduction
- Machine Learning
- Deep Learning
- Neural Networks
- Partial Differential Equations
- Stochastic Gradient Descent
- Self-Organizing Maps
- Transfer Learning
- Parallel Computing
- Tensor Decomposition
- Gaussian Processes
- Variational Inference
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 19 words, with their numbers
- Deep Learning355 topics
- Machine Learning224 topics
- Neural Networks203 topics
- Model Reduction121 topic
- Partial Differential Equations121 topic
- Random Projections91 topic
- Stochastic Gradient Descent91 topic
- Backpropagation Learning81 topic
- Self-Organizing Maps81 topic
- Domain Adaptation51 topic
- Transfer Learning51 topic
- Multilinear Algebra41 topic
- Parallel Computing41 topic
- Performance Optimization41 topic
- Tensor Decomposition41 topic
- Adversarial Examples31 topic
- Gaussian Processes31 topic
- Robustness31 topic
- Variational Inference31 topic
Where does Felix Dangel work?
Felix Dangel's main affiliation in the publication record is Vector Institute, Canada.
How many publications and citations does Felix Dangel have?
OpenAlex counts 37 works and 149 citations for Felix Dangel, an h-index of 3, ranking #4,082,359 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.
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