Preconditioning Kernel Matrices. - Kurt Cutajar; Michael A. Osborne; John P. Cunningham; Maurizio Filippone (ICML, 2016)

Random Feature Expansions for Deep Gaussian Processes. - Kurt Cutajar; Edwin V. Bonilla; Pietro Michiardi; Maurizio Filippone (ICML, 2017)

Entropic Trace Estimates for Log Determinants. - Jack K. Fitzsimons; Diego Granziol; Kurt Cutajar; Michael A. Osborne; Maurizio Filippone; Stephen J. Roberts (ECML/PKDD (1), 2017)

Bayesian Inference of Log Determinants. - Jack K. Fitzsimons; Kurt Cutajar; Maurizio Filippone; Michael A. Osborne; Stephen J. Roberts (UAI, 2017)

AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models. - Karl Krauth; Edwin V. Bonilla; Kurt Cutajar; Maurizio Filippone (UAI, 2017)

Deep Gaussian Processes for Multi-fidelity Modeling. - Kurt Cutajar; Mark Pullin; Andreas C. Damianou; Neil D. Lawrence; Javier González 002 (CoRR, 2019)

Broadening the scope of gaussian processes for large-scale learning. (Élargir la portée des processus gaussiens pour l'apprentissage à grande échelle). - Kurt Cutajar (2019)

Low-Count Time Series Anomaly Detection. - Philipp Renz; Kurt Cutajar; Niall Twomey; Gavin K. C. Cheung; Hanting Xie (MLSP, 2023)

Inherently Interpretable Time Series Classification via Multiple Instance Learning. - Joseph Early; Gavin K. C. Cheung; Kurt Cutajar; Hanting Xie; Jas Kandola; Niall Twomey (ICLR, 2024)