Vladislav Polianskii

According to our database, Vladislav Polianskii authored at least 9 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

InvMap and Witness Simplicial Variational Auto-Encoders.

Aniss Aiman Medbouhi, Vladislav Polianskii, Anastasia Varava, Danica Kragic

Mach. Learn. Knowl. Extr., March, 2023

An Efficient and Continuous Voronoi Density Estimator.

Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Breaking the Dimensionality Curse of Voronoi Tessellations.

Vladislav Polianskii

PhD thesis, 2022

Delaunay Component Analysis for Evaluation of Data Representations.

Petra Poklukar, Vladislav Polianskii, Anastasia Varava, Florian T. Pokorny, Danica Kragic

CoRR, 2022

Voronoi density estimator for high-dimensional data: Computation, compactification and convergence.

Vladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg, Anastasiia Varava, Florian T. Pokorny, Danica Kragic

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Active Nearest Neighbor Regression Through Delaunay Refinement.

Alexander Kravberg, Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic

Proceedings of the International Conference on Machine Learning, 2022

Delaunay Component Analysis for Evaluation of Data Representations.

Petra Poklukar, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

Voronoi Graph Traversal in High Dimensions with Applications to Topological Data Analysis and Piecewise Linear Interpolation.

Vladislav Polianskii, Florian T. Pokorny

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

Voronoi Boundary Classification: A High-Dimensional Geometric Approach via Weighted Monte Carlo Integration.

Vladislav Polianskii, Florian T. Pokorny

Proceedings of the 36th International Conference on Machine Learning, 2019