Simon O'Callaghan
Simon O'Callaghan
Principal Researcher at Gradient Institute
Verified email at
Cited by
Cited by
Gaussian process occupancy maps
ST O’Callaghan, FT Ramos
The International Journal of Robotics Research 31 (1), 42-62, 2012
Contextual occupancy maps using Gaussian processes
S O'Callaghan, FT Ramos, H Durrant-Whyte
2009 IEEE International Conference on Robotics and Automation, 1054-1060, 2009
Census of seafloor sediments in the world’s ocean
A Dutkiewicz, RD Müller, S O’Callaghan, H Jónasson
Geology 43 (9), 795-798, 2015
Learning navigational maps by observing human motion patterns
ST O'Callaghan, SPN Singh, A Alempijevic, FT Ramos
2011 IEEE International Conference on Robotics and Automation, 4333-4340, 2011
The impact of computerisation and automation on future employment
H Durrant-Whyte, L McCalman, S O’Callaghan, A Reid, D Steinberg
Australia’s future workforce, 56-64, 2015
Predicting Spatio-Temporal Propagation of Seasonal Influenza Using Variational Gaussian Process Regression.
R Senanayake, OC Simon Timothy, F Ramos
AAAI, 3901-3907, 2016
Continuous occupancy mapping with integral kernels
ST O'Callaghan, FT Ramos
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence …, 2011
Multi-modal estimation with kernel embeddings for learning motion models
L McCalman, S O'Callaghan, F Ramos
2013 IEEE International Conference on Robotics and Automation, 2845-2852, 2013
Contextual occupancy maps incorporating sensor and location uncertainty
ST O'Callaghan, FT Ramos, H Durrant-Whyte
2010 IEEE International Conference on Robotics and Automation, 3478-3485, 2010
Spatio-temporal hilbert maps for continuous occupancy representation in dynamic environments
R Senanayake, L Ott, S O'Callaghan, FT Ramos
Advances in Neural Information Processing Systems, 3925-3933, 2016
Gaussian process occupancy maps for dynamic environments
ST O’Callaghan, FT Ramos
Experimental Robotics, 791-805, 2016
Predicting sediment thickness on vanished ocean crust since 200 Ma
A Dutkiewicz, RD Müller, X Wang, S O'callaghan, J Cannon, NM Wright
Geochemistry, Geophysics, Geosystems 18 (12), 4586-4603, 2017
Bayesian joint inversions for the exploration of earth resources
AS Reid, S O’Callaghan, E Bonilla, L McCalman, T Rawling, F Ramos
Twenty-Third International Joint Conference on Artificial Intelligence, 2013
Learning highly dynamic environments with stochastic variational inference
R Senanayake, S O'Callaghan, F Ramos
2017 IEEE International Conference on Robotics and Automation (ICRA), 2532-2539, 2017
Distributed Bayesian Geophysical Inversions
L McCalman, ST O’Callaghan, A Reid, D Shen, S Carter, L Krieger, ...
Controls on the distribution of deep‐sea sediments
A Dutkiewicz, S O'Callaghan, RD Müller
Geochemistry, Geophysics, Geosystems 17 (8), 3075-3098, 2016
Australia’s future workforce
H Durrant-Whyte, L McCalman, S O’Callaghan, A Reid, D Steinberg
The Committee for Economic Development of Australia, 60, 2015
A Bayesian inference tool for geophysical joint inversions
G Beardsmore, H Durrant-Whyte, L McCALMAN, S O’Callaghan, A Reid
ASEG Extended Abstracts 2016 (1), 1-10, 2016
Fast Fair Regression via Efficient Approximations of Mutual Information
D Steinberg, A Reid, S O'Callaghan, F Lattimore, L McCalman, T Caetano
arXiv preprint arXiv:2002.06200, 2020
Fairness Measures for Regression via Probabilistic Classification
D Steinberg, A Reid, S O'Callaghan
arXiv preprint arXiv:2001.06089, 2020
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