Mark van der Wilk

Imperial College London

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Architecture Design (Transformers, SSMs, MoE) (1)Distributed Systems & Hardware (1)Training Efficiency & Optimization (1)

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Stefano Cortinovis (1)Laurence Aitchison (1)J. Hensman (1)S. No (1)

Papers (1)

Apr 1, 2026

Inverse-Free Sparse Variational Gaussian Processes

Ditch the Cholesky decomposition: this work makes Sparse Variational Gaussian Processes (SVGPs) matrix-multiply friendly, unlocking faster and more scalable GP training on modern hardware.

Stefano Cortinovis, Laurence Aitchison, J. Hensman +2

Architecture Design (Transformers, SSMs, MoE)Distributed Systems & Hardware Training Efficiency & Optimization

Mark van der Wilk

Research focus

Frequent co-authors

Papers (1)

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Mark van der Wilk

Research focus

Frequent co-authors

Papers (1)