Alexandre K. W. Navarro
Papers
3
Total Citations
19
H-Index
2
About
Alexandre K. W. Navarro is a researcher whose work focuses on advancing probabilistic modelling for circular data—a domain often overlooked in machine learning despite its relevance to fields as diverse as robotics, biology, and the social sciences. His major contribution is the development of the Multivariate Generalised von Mises distribution, a powerful framework that extends standard probabilistic tools to handle circular variables. This work, detailed in his most-cited papers (2016–2017), provides robust inference methods and real-world applications, enabling more accurate modelling of directional data such as angles, orientations, and periodic patterns. With a combined citation count of 19 across his top papers, Navarro’s research is a foundational step toward integrating circular statistics into mainstream machine learning. His efforts help bridge a critical gap, offering practitioners new ways to analyze complex, cyclical phenomena—from robotic movement to social behavior—making his contributions both technically innovative and practically impactful for students and researchers tackling non-Euclidean data.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3The Multivariate Generalised von Mises: Inference and applications2 citations · 2016