Preprint
Machine Learning
|

Residual Deep Gaussian Processes on Manifolds

K. Wyrwal, A. Krause, V. Borovitskiy

PDF arXiv Code

Preprint
Machine Learning
Software
|

The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs

P. Mostowsky, V. Dutordoir, I. Azangulov, N. Jaquier, M. Hutchinson, A. Ravuri, L. Rozo, A. Terenin, V. Borovitskiy

PDF arXiv Code

Published
Machine Learning
|

Intrinsic Gaussian Vector Fields on Manifolds

D. Robert-Nicoud, A. Krause, V. Borovitskiy

In International Conference on Artificial Intelligence and Statistics (AISTATS), 2024

Oral

PDF arXiv In Proceedings Code

Published
Machine Learning
|

Hodge-Compositional Edge Gaussian Processes

M. Yang, V. Borovitskiy, E. Isufi

In International Conference on Artificial Intelligence and Statistics (AISTATS), 2024

PDF arXiv In Proceedings Code

Published
Machine Learning
Statistics
|

Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces

I. Azangulov, A. Smolensky, A. Terenin, V. Borovitskiy

In Journal of Machine Learning Research (JMLR), 2024

PDF arXiv Link Code

Published
Machine Learning
Statistics
|

Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case

I. Azangulov, A. Smolensky, A. Terenin, V. Borovitskiy

In Journal of Machine Learning Research (JMLR), 2024

PDF arXiv Link Code

Published
Robotics
Machine Learning
|

Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifolds

N. Jaquier, L. Rozo, M. González-Duque, V. Borovitskiy, T. Asfour

In International Conference on Machine Learning (ICML), 2024

PDF arXiv In Proceedings Code

Published
Machine Learning
Statistics
|

Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds

P. Rosa, V. Borovitskiy, A. Terenin, J. Rousseau

In Neural Information Processing Systems (NeurIPS), 2023

Spotlight

PDF arXiv In Proceedings Code

Published
Machine Learning
|

Implicit Manifold Gaussian Process Regression

B. Fichera, V. Borovitskiy, A. Krause, A. Billard

In Neural Information Processing Systems (NeurIPS), 2023

PDF arXiv In Proceedings Code

Published
Machine Learning
|

Isotropic Gaussian Processes on Finite Spaces of Graphs

V. Borovitskiy, M. R. Karimi, V. R. Somnath, A. Krause

In International Conference on Artificial Intelligence and Statistics (AISTATS), 2023

PDF arXiv Code In Proceedings

Published
Bioinformatics
Optimization
Machine Learning
|

Bayesian optimization for demographic inference

E. Noskova, V. Borovitskiy

In G3: Genes, Genomes, Genetics, 2023

Link PDF bioRxiv Code

Short note
Machine Learning
|

On power sum kernels on symmetric groups

I. Azangulov, V. Borovitskiy, A. Smolensky

PDF arXiv

Published
Harmonic Analysis
|

Littlewood–Paley–Rubio de Francia inequality for multi-parameter Vilenkin systems

V. Borovitskiy

In Mathematische Nachrichten, 2023

Link PDF arXiv

Published
Machine Learning
|

Quadric hypersurface intersection for manifold learning in feature space

F. Pavutnitskiy, S. O. Ivanov, E. Abramov, V. Borovitskiy, A. Klochkov, V. Vialov, A. Zaikovskii, A. Petiushko

In International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

PDF Code arXiv In Proceedings

Published
Harmonic Analysis
|

Burkholder meets Gundy: Bellman function method for general operators on martingales

V. Borovitskiy, N. Osipov, A. Tselishchev

In Advances in Mathematics, 2022

Link arXiv PDF arXiv Short announcement

Published
Harmonic Analysis
|

Interpolation of abstract Hardy-type spaces

V. Borovitskiy, S. Kislyakov

In Journal of Mathematical Sciences, 2022

Link Russian version

Published
Harmonic Analysis
|

Littlewood–Paley–Rubio De Francia Inequality for the Two-Parameter Walsh System

V. Borovitskiy

In Journal of Mathematical Sciences, 2022

Link Preprint Russian version

Published
Machine Learning
|

Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels

M. Hutchinson, A. Terenin, V. Borovitskiy, S. Takao, Y. W. Teh, M. P. Deisenroth,

In Neural Information Processing Systems (NeurIPS), 2021

PDF Code arXiv In Proceedings

Published
Robotics
Optimization
Machine Learning
|

Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels

N. Jaquier, V. Borovitskiy, A. Smolensky, A. Terenin, T. Asfour, L. Rozo,

In Conference on Robot Learning (CoRL), 2022

PDF Code arXiv In Proceedings

Published
Machine Learning
|

Matérn Gaussian Processes on Graphs

V. Borovitskiy, I. Azangulov, A. Terenin, P. Mostowsky, M. P. Deisenroth, N. Durrande

In International Conference on Artificial Intelligence and Statistics (AISTATS), 2021

Best Student Paper Award

PDF Code arXiv In Proceedings

Published
Machine Learning
|

Pathwise Conditioning of Gaussian Processes

J. T. Wilson, V. Borovitskiy, A. Terenin, P. Mostowsky, M. P. Deisenroth

In Journal of Machine Learning Research (JMLR), 2021

PDF arXiv Link

Published
Harmonic Analysis
|

Weighted Littlewood–Paley inequality for arbitrary rectangles in \(\mathbb{R}^2\)

V. Borovitskiy

In St. Petersburg Mathematical Journal, 2021

Link Russian version

Published
Geostatistics
|

Boolean Spectral Analysis in Categorical Reservoir Modeling

N. Ismagilov, V. Borovitskiy, M. Lifshits, M. Platonova

In Mathematical Geosciences, 2021

Link Earlier Non Peer-reviewed Conference Version

Published
Machine Learning
|

Matérn Gaussian processes on Riemannian manifolds

V. Borovitskiy, A. Terenin, P. Mostowsky, M. P. Deisenroth

In Neural Information Processing Systems (NeurIPS), 2020

PDF Code arXiv In Proceedings

Published
Machine Learning
|

Efficiently sampling functions from Gaussian process posteriors

J. T. Wilson, V. Borovitskiy, A. Terenin, P. Mostowsky, M. P. Deisenroth

In International Conference on Machine Learning (ICML), 2020

Outstanding Paper Honorable Mention

PDF Code arXiv In Proceedings

Non peer-reviewed
Geostatistics
|

Bayesian Inference of Covariance Parameters in Spectral Approach to Geostatistical Simulation

N. Ismagilov, I. Azangulov, V. Borovitskiy, M. Lifshits, P. Mostowsky

In European Conference on the Mathematics of Oil Recovery (ECMOR), 2020

Link

Non peer-reviewed
Machine Learning
|

Reproducibility Project: DeepSite

T. Malygina, V. Borovitskiy, Y. Porozov

In Transylvanian Machine Learning Summer School, 2018

Link Code

Published
Harmonic Analysis
|

K-closedness for weighted Hardy spaces on the torus \(\mathbb{T}^2\).

V. Borovitskiy

In Journal of Mathematical Sciences, 2018

Link Russian version