Kurt Cutajar

According to our database, Kurt Cutajar authored at least 9 papers between 2016 and 2023.

Collaborative distances:

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

2023

Inherently Interpretable Time Series Classification via Multiple Instance Learning.

Joseph Early, Gavin K. C. Cheung, Kurt Cutajar, Hanting Xie, Jas Kandola, Niall Twomey

CoRR, 2023

Low-Count Time Series Anomaly Detection.

Philipp Renz, Kurt Cutajar, Niall Twomey, Gavin K. C. Cheung, Hanting Xie

Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

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

PhD thesis, 2019

Deep Gaussian Processes for Multi-fidelity Modeling.

Kurt Cutajar, Mark Pullin, Andreas C. Damianou, Neil D. Lawrence, Javier González

CoRR, 2019

2017

AutoGP: Exploring the Capabilities and Limitations of Gaussian Process Models.

Karl Krauth, Edwin V. Bonilla, Kurt Cutajar, Maurizio Filippone

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Bayesian Inference of Log Determinants.

Jack K. Fitzsimons, Kurt Cutajar, Maurizio Filippone, Michael A. Osborne, Stephen J. Roberts

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Entropic Trace Estimates for Log Determinants.

Jack K. Fitzsimons, Diego Granziol, Kurt Cutajar, Michael A. Osborne, Maurizio Filippone, Stephen J. Roberts

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Random Feature Expansions for Deep Gaussian Processes.

Kurt Cutajar, Edwin V. Bonilla, Pietro Michiardi, Maurizio Filippone

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Preconditioning Kernel Matrices.

Kurt Cutajar, Michael A. Osborne, John P. Cunningham, Maurizio Filippone

Proceedings of the 33nd International Conference on Machine Learning, 2016