Efficient Gaussian Neural Processes for Regression. - Stratis Markou; James Requeima; Wessel P. Bruinsma; Richard E. Turner (CoRR, 2021)

Practical Conditional Neural Process Via Tractable Dependent Predictions. - Stratis Markou; James Requeima; Wessel P. Bruinsma; Anna Vaughan; Richard E. Turner (ICLR, 2022)

Fast Relative Entropy Coding with A* coding. - Gergely Flamich; Stratis Markou; José Miguel Hernández-Lobato (ICML, 2022)

Practical Conditional Neural Processes Via Tractable Dependent Predictions. - Stratis Markou; James Requeima; Wessel P. Bruinsma; Anna Vaughan; Richard E. Turner (CoRR, 2022)

Active Learning with Convolutional Gaussian Neural Processes for Environmental Sensor Placement. - Tom R. Andersson; Wessel P. Bruinsma; Stratis Markou; James Requeima; Alejandro Coca-Castro; Anna Vaughan; Anna-Louise Ellis; Matthew Lazzara; Daniel C. Jones; J. Scott Hosking; Richard E. Turner (CoRR, 2022)

Autoregressive Conditional Neural Processes. - Wessel P. Bruinsma; Stratis Markou; James Requeima; Andrew Y. K. Foong; Tom R. Andersson; Anna Vaughan; Anthony Buonomo; J. Scott Hosking; Richard E. Turner (ICLR, 2023)

Faster Relative Entropy Coding with Greedy Rejection Coding. - Gergely Flamich; Stratis Markou; José Miguel Hernández-Lobato (NeurIPS, 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; et al. (CoRR, 2023)

Translation Equivariant Transformer Neural Processes. - Matthew Ashman; Cristiana Diaconu; Junhyuck Kim; Lakee Sivaraya; Stratis Markou; James Requeima; Wessel P. Bruinsma; Richard E. Turner (ICML, 2024)

Noise-Aware Differentially Private Regression via Meta-Learning. - Ossi Räisä; Stratis Markou; Matthew Ashman; Wessel P. Bruinsma; Marlon Tobaben; Antti Honkela; Richard E. Turner (NeurIPS, 2024)

Denoising Diffusion Probabilistic Models in Six Simple Steps. - Richard E. Turner; Cristiana-Diana Diaconu; Stratis Markou; Aliaksandra Shysheya; Andrew Y. K. Foong; Bruno Mlodozeniec (CoRR, 2024)

Aardvark Weather: end-to-end data-driven weather forecasting. - Anna Vaughan; Stratis Markou; Will Tebbutt; James Requeima; Wessel P. Bruinsma; Tom R. Andersson; Michael Herzog; Nicholas D. Lane; J. Scott Hosking; Richard E. Turner (CoRR, 2024)

Variance-Reducing Couplings for Random Features: Perspectives from Optimal Transport. - Isaac Reid; Stratis Markou; Krzysztof Choromanski; Richard E. Turner; Adrian Weller (CoRR, 2024)

Variance-Reducing Couplings for Random Features. - Isaac Reid; Stratis Markou; Krzysztof Marcin Choromanski; Richard E. Turner; Adrian Weller (ICLR, 2025)

End-to-end data-driven weather prediction. - Anna Allen; Stratis Markou; Will Tebbutt; James Requeima; Wessel P. Bruinsma; Tom R. Andersson; Michael Herzog; Nicholas D. Lane; Matthew Chantry; J. Scott Hosking; Richard E. Turner (Nat., 2025)

Skillful joint probabilistic weather forecasting from marginals. - Ferran Alet; Ilan Price; Andrew El-Kadi; Dominic Masters; Stratis Markou; Tom R. Andersson; Jacklynn Stott; Rémi Lam; Matthew Willson; Alvaro Sanchez-Gonzalez; Peter W. Battaglia (CoRR, 2025)