Alexander Terenin

52 papers A* 9A 6Misc 1Journal 35Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	An Adversarial Analysis of Thompson Sampling for Full-information Online Learning: from Finite to Infinite Action Spaces. CoRR Alexander Terenin, Jeffrey Negrea
2025	J	`jnl`	Cost-aware Stopping for Bayesian Optimization. CoRR Qian Xie, Linda Cai, Alexander Terenin, Peter I. Frazier, Ziv Scully
2025	A*	`conf`	Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes. ICML Sidhanth Holalkere, David Bindel, Silvia Sellán, Alexander Terenin
2025	J	`jnl`	Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes. CoRR Sidhanth Holalkere, David S. Bindel, Silvia Sellán, Alexander Terenin
2025	J	`jnl`	The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs. J. Mach. Learn. Res. Peter Mostowsky, Vincent Dutordoir, Iskander Azangulov, Noémie Jaquier, Michael John Hutchinson, Aditya Ravuri, Leonel Rozo, Alexander Terenin, Viacheslav Borovitskiy
2025	J	`jnl`	The Gittins Index: A Design Principle for Decision-Making Under Uncertainty. CoRR Ziv Scully, Alexander Terenin
2024	A	`conf`	A Unifying Variational Framework for Gaussian Process Motion Planning. AISTATS Lucas Cosier, Rares Iordan, Sicelukwanda N. T. Zwane, Giovanni Franzese, James T. Wilson, Marc Peter Deisenroth, Alexander Terenin, Yasemin Bekiroglu
2024	A*	`conf`	Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index. NeurIPS Qian Xie, Raul Astudillo, Peter I. Frazier, Ziv Scully, Alexander Terenin
2024	J	`jnl`	Cost-aware Bayesian optimization via the Pandora's Box Gittins index. CoRR Qian Xie, Raul Astudillo, Peter I. Frazier, Ziv Scully, Alexander Terenin
2024	J	`jnl`	Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees. J. Mach. Learn. Res. Alexander Terenin, David R. Burt, Artem Artemev, Seth R. Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge
2024	J	`jnl`	Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case. J. Mach. Learn. Res. Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy
2024	J	`jnl`	Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces. J. Mach. Learn. Res. Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy
2024	A*	`conf`	Stochastic Gradient Descent for Gaussian Processes Done Right. ICLR Jihao Andreas Lin, Shreyas Padhy, Javier Antorán, Austin Tripp, Alexander Terenin, Csaba Szepesvári, José Miguel Hernández-Lobato, David Janz
2024	J	`jnl`	The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs. CoRR Peter Mostowsky, Vincent Dutordoir, Iskander Azangulov, Noémie Jaquier, Michael John Hutchinson, Aditya Ravuri, Leonel Rozo, Alexander Terenin, Viacheslav Borovitskiy
2023	J	`jnl`	A Unifying Variational Framework for Gaussian Process Motion Planning. CoRR Lucas Cosier, Rares Iordan, Sicelukwanda Zwane, Giovanni Franzese, James T. Wilson, Marc Peter Deisenroth, Alexander Terenin, Yasemin Bekiroglu
2023	A*	`conf`	Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds. NeurIPS Paul Rosa, Slava Borovitskiy, Alexander Terenin, Judith Rousseau
2023	J	`jnl`	Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds. CoRR Paul Rosa, Viacheslav Borovitskiy, Alexander Terenin, Judith Rousseau
2023	A*	`conf`	Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent. NeurIPS Jihao Andreas Lin, Javier Antorán, Shreyas Padhy, David Janz, José Miguel Hernández-Lobato, Alexander Terenin
2023	J	`jnl`	Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent. CoRR Jihao Andreas Lin, Javier Antorán, Shreyas Padhy, David Janz, José Miguel Hernández-Lobato, Alexander Terenin
2023	J	`jnl`	Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces. CoRR Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy
2023	J	`jnl`	Stochastic Gradient Descent for Gaussian Processes Done Right. CoRR Jihao Andreas Lin, Shreyas Padhy, Javier Antorán, Austin Tripp, Alexander Terenin, Csaba Szepesvári, José Miguel Hernández-Lobato, David Janz
2023	A*	`conf`	The Cambridge Law Corpus: A Corpus for Legal AI Research. NeurIPS Andreas Östling, Holli Sargeant, Huiyuan Xie, Ludwig Bull, Alexander Terenin, Leif Jonsson, Måns Magnusson, Felix Steffek
2023	J	`jnl`	The Cambridge Law Corpus: A Corpus for Legal AI Research. CoRR Andreas Östling, Holli Sargeant, Huiyuan Xie, Ludwig Bull, Alexander Terenin, Leif Jonsson, Måns Magnusson, Felix Steffek
2022	J	`jnl`	Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces. CoRR Alexander Terenin
2022	J	`jnl`	Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees. CoRR Alexander Terenin, David R. Burt, Artem Artemev, Seth R. Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge
2022	J	`jnl`	Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the Compact Case. CoRR Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy
2021	A	`conf`	Aligning Time Series on Incomparable Spaces. AISTATS Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
2021	Misc	`conf`	Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels. CoRL Noémie Jaquier, Viacheslav Borovitskiy, Andrei Smolensky, Alexander Terenin, Tamim Asfour, Leonel Dario Rozo
2021	J	`jnl`	Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels. CoRR Noémie Jaquier, Viacheslav Borovitskiy, Andrei Smolensky, Alexander Terenin, Tamim Asfour, Leonel Dario Rozo
2021	A	`conf`	Learning Contact Dynamics using Physically Structured Neural Networks. AISTATS Andreas Hochlehnert, Alexander Terenin, Steindór Sæmundsson, Marc Peter Deisenroth
2021	J	`jnl`	Learning Contact Dynamics using Physically Structured Neural Networks. CoRR Andreas Hochlehnert, Alexander Terenin, Steindór Sæmundsson, Marc Peter Deisenroth
2021	A	`conf`	Matérn Gaussian Processes on Graphs. AISTATS Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande
2021	J	`jnl`	Pathwise Conditioning of Gaussian Processes. J. Mach. Learn. Res. James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2021	J	`jnl`	Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Equivariant Projected Kernels. CoRR Michael J. Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth
2021	A*	`conf`	Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels. NeurIPS Michael J. Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth
2020	J	`jnl`	Aligning Time Series on Incomparable Spaces. CoRR Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
2020	A	`conf`	Asynchronous Gibbs Sampling. AISTATS Alexander Terenin, Daniel Simpson, David Draper
2020	A*	`conf`	Efficiently sampling functions from Gaussian process posteriors. ICML James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	J	`jnl`	Efficiently sampling functions from Gaussian process posteriors. CoRR James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	J	`jnl`	Matern Gaussian Processes on Graphs. CoRR Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande
2020	J	`jnl`	Matern Gaussian processes on Riemannian manifolds. CoRR Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	A*	`conf`	Matérn Gaussian Processes on Riemannian Manifolds. NeurIPS Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	J	`jnl`	Pathwise Conditioning of Gaussian Processes. CoRR James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
2020	—	`conf`	Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models. EMNLP (1) Alexander Terenin, Måns Magnusson, Leif Jonsson
2020	A	`conf`	Variational Integrator Networks for Physically Structured Embeddings. AISTATS Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
2019	J	`jnl`	GPU-accelerated Gibbs sampling: a case study of the Horseshoe Probit model. Stat. Comput. Alexander Terenin, Shawfeng Dong, David Draper
2019	J	`jnl`	Pólya Urn Latent Dirichlet Allocation: A Doubly Sparse Massively Parallel Sampler. IEEE Trans. Pattern Anal. Mach. Intell. Alexander Terenin, Måns Magnusson, Leif Jonsson, David Draper
2019	J	`jnl`	Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models. CoRR Alexander Terenin, Måns Magnusson, Leif Jonsson
2019	J	`jnl`	Variational Integrator Networks for Physically Meaningful Embeddings. CoRR Steindór Sæmundsson, Alexander Terenin, Katja Hofmann, Marc Peter Deisenroth
2017	J	`jnl`	A Noninformative Prior on a Space of Distribution Functions. Entropy Alexander Terenin, David Draper
2017	J	`jnl`	Techniques for proving Asynchronous Convergence results for Markov Chain Monte Carlo methods. CoRR Alexander Terenin, Eric P. Xing
2016	J	`jnl`	GPU-accelerated Gibbs Sampling. CoRR Alexander Terenin, Shawfeng Dong, David Draper