Terenin, Alexander

20 publications

ICML 2025 Stochastic Poisson Surface Reconstruction with One Solve Using Geometric Gaussian Processes Sidhanth Holalkere, David Bindel, Silvia Sellán, Alexander Terenin

AISTATS 2024 A Unifying Variational Framework for Gaussian Process Motion Planning Lucas C. Cosier, Rares Iordan, Sicelukwanda N. T. Zwane, Giovanni Franzese, James T. Wilson, Marc Deisenroth, Alexander Terenin, Yasemin Bekiroglu

NeurIPS 2024 Cost-Aware Bayesian Optimization via the Pandora's Box Gittins Index Qian Xie, Raul Astudillo, Peter I. Frazier, Ziv Scully, Alexander Terenin

JMLR 2024 Numerically Stable Sparse Gaussian Processes via Minimum Separation Using Cover Trees Alexander Terenin, David R. Burt, Artem Artemev, Seth Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge

JMLR 2024 Stationary Kernels and Gaussian Processes on Lie Groups and Their Homogeneous Spaces I: The Compact Case Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy

JMLR 2024 Stationary Kernels and Gaussian Processes on Lie Groups and Their Homogeneous Spaces II: Non-Compact Symmetric Spaces Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy

ICLR 2024 Stochastic Gradient Descent for Gaussian Processes Done Right Jihao Andreas Lin, Shreyas Padhy, Javier Antoran, Austin Tripp, Alexander Terenin, Csaba Szepesvari, José Miguel Hernández-Lobato, David Janz

NeurIPS 2023 Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds Paul Rosa, Slava Borovitskiy, Alexander Terenin, Judith Rousseau

NeurIPS 2023 Sampling from Gaussian Process Posteriors Using Stochastic Gradient Descent Jihao Andreas Lin, Javier Antorán, Shreyas Padhy, David Janz, José Miguel Hernández-Lobato, Alexander Terenin

NeurIPS 2023 The Cambridge Law Corpus: A Dataset for Legal AI Research Andreas Östling, Holli Sargeant, Huiyuan Xie, Ludwig Bull, Alexander Terenin, Leif Jonsson, Måns Magnusson, Felix Steffek

AISTATS 2021 Aligning Time Series on Incomparable Spaces Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Deisenroth

AISTATS 2021 Learning Contact Dynamics Using Physically Structured Neural Networks Andreas Hochlehnert, Alexander Terenin, Steindor Saemundsson, Marc Deisenroth

AISTATS 2021 Matérn Gaussian Processes on Graphs Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Deisenroth, Nicolas Durrande

CoRL 2021 Geometry-Aware Bayesian Optimization in Robotics Using Riemannian Matérn Kernels Noémie Jaquier, Viacheslav Borovitskiy, Andrei Smolensky, Alexander Terenin, Tamim Asfour, Leonel Rozo

JMLR 2021 Pathwise Conditioning of Gaussian Processes James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth

NeurIPS 2021 Vector-Valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels Michael Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee W. Teh, Marc Deisenroth

AISTATS 2020 Asynchronous Gibbs Sampling Alexander Terenin, Daniel Simpson, David Draper

ICML 2020 Efficiently Sampling Functions from Gaussian Process Posteriors James Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Deisenroth

NeurIPS 2020 Matérn Gaussian Processes on Riemannian Manifolds Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Deisenroth

AISTATS 2020 Variational Integrator Networks for Physically Structured Embeddings Steindor Saemundsson, Alexander Terenin, Katja Hofmann, Marc Deisenroth