Alexander Terenin
PhD (10/2018-11/2021)
Imperial College London
Interests
- Machine learning
- Bayesian theory
- Geometric machine learning
Blog posts
- Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels (Dec 2021)
- Matérn Gaussian Processes on Graphs (Apr 2021)
- Learning Contact Dynamics using Physically Structured Neural Networks (Aug 2020)
- Variational Integrator Networks (Aug 2020)
- Aligning Time Series on Incomparable Space (Jul 2020)
- Efficiently Sampling Functions from Gaussian Process Posteriors (Jul 2020)
- Matérn Gaussian Processes on Riemannian Manifolds (Jun 2020)
Publications
- A Unifying Variational Framework for Gaussian Process Motion Planning (2024)
- Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels (2021)
- Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels (2021)
- Pathwise Conditioning of Gaussian Processes (2021)
- Aligning Time Series on Incomparable Spaces (2021)
- Learning Contact Dynamics using Physically Structured Neural Networks (2021)
- Matérn Gaussian Processes on Graphs (2021)
- Matérn Gaussian Processes on Riemannian Manifolds (2020)
- Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models (2020)
- Efficiently Sampling Functions from Gaussian Process Posteriors (2020)
- Aligning Time Series on Incomparable Spaces (2020)
- Variational Integrator Networks for Physically Structured Embeddings (2020)
- Asynchronous Gibbs Sampling (2020)
- Variational Integrator Networks for Physically Meaningful Embeddings (2019)