Robert Allison

According to our database, Robert Allison authored at least 6 papers between 2022 and 2026.

Collaborative distances:

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

2026

The Theory and Practice of Highly Scalable Gaussian Process Regression with Nearest Neighbours.

Robert Allison, Tomasz Maciazek, Anthony Stephenson

CoRR, April, 2026

2025

Bilateral Distribution Compression: Reducing Both Data Size and Dimensionality.

Dominic Broadbent, Nick Whiteley, Robert Allison, Tom Lovett

CoRR, September, 2025

Vulnerability of Transfer-Learned Neural Networks to Data Reconstruction Attacks in Small-Data Regime.

Tomasz Maciazek, Robert Allison

CoRR, May, 2025

Conditional Distribution Compression via the Kernel Conditional Mean Embedding.

Dominic Broadbent, Nick Whiteley, Robert Allison, Tom Lovett

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2023

Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression.

Robert Allison, Anthony Stephenson, Samuel F, Edward O. Pyzer-Knapp

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Provably Reliable Large-Scale Sampling from Gaussian Processes.

Anthony Stephenson, Robert Allison, Edward Pyzer-Knapp

CoRR, 2022