Artem Artemev

According to our database, Artem Artemev authored at least 17 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Recommendations for Baselines and Benchmarking Approximate Gaussian Processes.

Sebastian W. Ober, Artem Artemev, Marcel Wagenländer, Rudolfs Grobins, Mark van der Wilk

CoRR, 2024

2023

Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow.

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

CoRR, 2023

2022

Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees.

Alexander Terenin, David R. Burt, Artem Artemev, Seth R. Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge

CoRR, 2022

Memory Safe Computations with XLA Compiler.

Artem Artemev, Tilman Roeder, Mark van der Wilk

CoRR, 2022

Memory safe computations with XLA compiler.

Artem Artemev, Yuze An, Tilman Roeder, Mark van der Wilk

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Barely Biased Learning for Gaussian Process Regression.

David R. Burt, Artem Artemev, Mark van der Wilk

CoRR, 2021

GPflux: A Library for Deep Gaussian Processes.

Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc Peter Deisenroth, S. T. John

CoRR, 2021

Scalable Thompson Sampling using Sparse Gaussian Process Models.

Sattar Vakili, Henry B. Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients.

Artem Artemev, David R. Burt, Mark van der Wilk

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Scalable Thompson Sampling using Sparse Gaussian Process Models.

Sattar Vakili, Victor Picheny, Artem Artemev

CoRR, 2020

A Framework for Interdomain and Multioutput Gaussian Processes.

Mark van der Wilk, Vincent Dutordoir, S. T. John, Artem Artemev, Vincent Adam, James Hensman

CoRR, 2020

Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation.

Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Bayesian Image Classification with Deep Convolutional Gaussian Processes.

Vincent Dutordoir, Mark van der Wilk, Artem Artemev, James Hensman

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Doubly Sparse Variational Gaussian Processes.

Vincent Adam, Stefanos Eleftheriadis, Artem Artemev, Nicolas Durrande, James Hensman

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Ordinal Bayesian Optimisation.

Victor Picheny, Sattar Vakili, Artem Artemev

CoRR, 2019

Translation Insensitivity for Deep Convolutional Gaussian Processes.

Vincent Dutordoir, Mark van der Wilk, Artem Artemev, Marcin Tomczak, James Hensman

CoRR, 2019

Variational Gaussian Process Models without Matrix Inverses.

Mark van der Wilk, S. T. John, Artem Artemev, James Hensman

Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019