Andreas Damianou
Andreas Damianou
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Title
Cited by
Cited by
Year
Deep Gaussian processes
A C. Damianou, N D. Lawrence
Proceedings of the Sixteenth International Workshop on Artificial …, 2013
5822013
Manifold relevance determination
A Damianou, CH Ek, M Titsias, N Lawrence
Proceedings of the 29th International Conference on Machine Learning, 145-152, 2012
1202012
Variational inference for latent variables and uncertain inputs in Gaussian processes
AC Damianou, MK Titsias, ND Lawrence
The Journal of Machine Learning Research 17 (1), 1425-1486, 2016
108*2016
Variational auto-encoded deep Gaussian processes
Z Dai, A Damianou, J González, N Lawrence
arXiv preprint arXiv:1511.06455, 2015
1002015
Variational gaussian process dynamical systems
A Damianou, MK Titsias, ND Lawrence
Advances in Neural Information Processing Systems, 2510-2518, 2011
922011
Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling
P Perdikaris, M Raissi, A Damianou, ND Lawrence, GE Karniadakis
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2017
772017
Deep Gaussian processes and variational propagation of uncertainty
A Damianou
University of Sheffield, 2015
762015
Recurrent gaussian processes
CLC Mattos, Z Dai, A Damianou, J Forth, GA Barreto, ND Lawrence
arXiv preprint arXiv:1511.06644, 2015
502015
Active learning for sparse bayesian multilabel classification
D Vasisht, A Damianou, M Varma, A Kapoor
Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014
452014
Variational information distillation for knowledge transfer
S Ahn, SX Hu, A Damianou, ND Lawrence, Z Dai
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
402019
Semi-described and semi-supervised learning with Gaussian processes
A Damianou, ND Lawrence
31st Conference on Uncertainty in Artificial Intelligence (UAI), 2015
292015
Gaussian process models with parallelization and GPU acceleration
Z Dai, A Damianou, J Hensman, N Lawrence
arXiv preprint arXiv:1410.4984, 2014
282014
Preferential bayesian optimization
J González, Z Dai, A Damianou, ND Lawrence
arXiv preprint arXiv:1704.03651, 2017
272017
An integrated probabilistic framework for robot perception, learning and memory
U Martinez-Hernandez, A Damianou, D Camilleri, LW Boorman, ...
2016 IEEE International Conference on Robotics and Biomimetics (ROBIO), 1796 …, 2016
222016
Leveraging crowdsourcing data for deep active learning an application: Learning intents in alexa
J Yang, T Drake, A Damianou, Y Maarek
Proceedings of the 2018 World Wide Web Conference, 23-32, 2018
202018
DAC-h3: a proactive robot cognitive architecture to acquire and express knowledge about the world and the self
C Moulin-Frier, T Fischer, M Petit, G Pointeau, JY Puigbo, U Pattacini, ...
IEEE Transactions on Cognitive and Developmental Systems 10 (4), 1005-1022, 2017
192017
Deep gaussian processes for multi-fidelity modeling
K Cutajar, M Pullin, A Damianou, N Lawrence, J González
arXiv preprint arXiv:1903.07320, 2019
162019
Multi-view learning as a nonparametric nonlinear inter-battery factor analysis
A Damianou, ND Lawrence, CH Ek
arXiv preprint arXiv:1604.04939, 2016
152016
Transferring knowledge across learning processes
S Flennerhag, PG Moreno, ND Lawrence, A Damianou
arXiv preprint arXiv:1812.01054, 2018
142018
Deep Gaussian processes with convolutional kernels
V Kumar, V Singh, PK Srijith, A Damianou
arXiv preprint arXiv:1806.01655, 2018
142018
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