Artem Artemev

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 20

Top Topics

Gaussian Process

Top Venues

Publications

Sebastian W. Ober, Artem Artemev, Marcel Wagenländer, Rudolfs Grobins, Mark van der Wilk
Recommendations for Baselines and Benchmarking Approximate Gaussian Processes. CoRR (2024)
Victor Picheny, Joel Berkeley, Henry B. Moss, Hrvoje Stojic, Uri Granta, Sebastian W. Ober, Artem Artemev, Khurram Ghani, Alexander Goodall, Andrei Paleyes, Sattar Vakili, Sergio Pascual-Diaz, Stratis Markou, Jixiang Qing, Nasrulloh R. B. S. Loka, Ivo Couckuyt
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow. CoRR (2023)
Artem Artemev, Tilman Roeder, Mark van der Wilk
Memory Safe Computations with XLA Compiler. CoRR (2022)
Alexander Terenin, David R. Burt, Artem Artemev, Seth Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees. CoRR (2022)
Artem Artemev, Yuze An, Tilman Roeder, Mark van der Wilk
Memory safe computations with XLA compiler. NeurIPS (2022)
Sattar Vakili, Henry B. Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny
Scalable Thompson Sampling using Sparse Gaussian Process Models. NeurIPS (2021)
Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc Peter Deisenroth, S. T. John
GPflux: A Library for Deep Gaussian Processes. CoRR (2021)
David R. Burt, Artem Artemev, Mark van der Wilk
Barely Biased Learning for Gaussian Process Regression. CoRR (2021)
Artem Artemev, David R. Burt, Mark van der Wilk
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients. CoRR (2021)
Artem Artemev, David R. Burt, Mark van der Wilk
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients. ICML (2021)
Sattar Vakili, Victor Picheny, Artem Artemev
Scalable Thompson Sampling using Sparse Gaussian Process Models. CoRR (2020)
Vincent Adam, Stefanos Eleftheriadis, Artem Artemev, Nicolas Durrande, James Hensman
Doubly Sparse Variational Gaussian Processes. AISTATS (2020)
Vincent Dutordoir, Mark van der Wilk, Artem Artemev, James Hensman
Bayesian Image Classification with Deep Convolutional Gaussian Processes. AISTATS (2020)
Vincent Adam, Stefanos Eleftheriadis, Nicolas Durrande, Artem Artemev, James Hensman
Doubly Sparse Variational Gaussian Processes. CoRR (2020)
Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. CoRR (2020)
Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. ECML/PKDD (3) (2020)
Mark van der Wilk, Vincent Dutordoir, S. T. John, Artem Artemev, Vincent Adam, James Hensman
A Framework for Interdomain and Multioutput Gaussian Processes. CoRR (2020)
Victor Picheny, Sattar Vakili, Artem Artemev
Ordinal Bayesian Optimisation. CoRR (2019)
Vincent Dutordoir, Mark van der Wilk, Artem Artemev, Marcin Tomczak, James Hensman
Translation Insensitivity for Deep Convolutional Gaussian Processes. CoRR (2019)
Mark van der Wilk, S. T. John, Artem Artemev, James Hensman
Variational Gaussian Process Models without Matrix Inverses. AABI (2019)