Viacheslav Borovitskiy
Lecturer in Machine Learning
Researches geometric machine learning, including Gaussian processes on manifolds and graphs.
Viacheslav Borovitskiy's lab at Edinburgh works on probabilistic & causal inference and geometry processing & modeling. 16 papers since 2023. 4 PhD students. 4 alumni.
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 0%
- PhD students
- 4
- MS students
- 0
- alumni listed
- 4
Papers by yearfrom the lab homepage, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 4 papers2025 · T1 0
- 5 papers2024 · T1 0
- 5 papers2023 · T1 0
T1 venuesOther
Research focuspaper titles that use each topic's words
- gaussian processes7 papers
- processes7 papers
- Probabilistic & causal inference2 papers
- Geometry processing & modeling0 papers
- geometric machine0 papers
Paper list
From the lab homepage.
20262 papers
- Accepted at Neural Information Processing Systems (NeurIPS)Patching Up Circuit Learning on Images
- Accepted at Neural Information Processing Systems (NeurIPS)Practical Non-Stationary Graph Gaussian Processes
20254 papers
- In Neural Information Processing Systems (NeurIPS)Omnipresent Yet Overlooked: Heat Kernels in Combinatorial Bayesian Optimization
- In Journal of Mathematical SciencesOn power sum kernels on symmetric groups
- In International Conference on Learning Representations (ICLR)Residual Deep Gaussian Processes on Manifolds
- In Machine Learning Open Source Software (MLOSS, part of JMLR)The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs
20245 papers
- In International Conference on Machine Learning (ICML)Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifolds
- In International Conference on Artificial Intelligence and Statistics (AISTATS)Hodge-Compositional Edge Gaussian Processes
- In International Conference on Artificial Intelligence and Statistics (AISTATS)Intrinsic Gaussian Vector Fields on Manifolds
- In Journal of Machine Learning Research (JMLR)Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case
- In Journal of Machine Learning Research (JMLR)Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces
20235 papers
- In G3: Genes, Genomes, GeneticsBayesian optimization for demographic inference
- In Neural Information Processing Systems (NeurIPS)Implicit Manifold Gaussian Process Regression
- In International Conference on Artificial Intelligence and Statistics (AISTATS)Isotropic Gaussian Processes on Finite Spaces of Graphs
- In Mathematische NachrichtenLittlewood–Paley–Rubio de Francia inequality for multi-parameter Vilenkin systems
- In Neural Information Processing Systems (NeurIPS)Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds
Where alumni went4 listed
Apply to EdinburghFall 2027
Not announced yet
Informatics PhD
- Round
- Rolling (funding consideration)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- none
Not yet confirmed for this intake.
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- The lab homepage
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