Freddie Kalaitzis
Cited by
Cited by
A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression
A Kalaitzis, ND Lawrence
BMC bioinformatics 12 (1), 180, 2011
Residual Component Analysis: Generalising PCA for more flexible inference in linear-Gaussian models
A Kalaitzis, ND Lawrence
Proceedings of the 29th International Conference on Machine Learning, 209–216, 2012
The Bigraphical Lasso
A Kalaitzis, J Lafferty, ND Lawrence, S Zhou
Proceedings of The 30th International Conference on Machine Learning 28 (3 …, 2013
A large-scale crowd-sourced analysis of abuse against women journalists and politicians on Twitter
L Delisle, A Kalaitzis, K Majewski, A de Berker, M Marin, J Cornebise
NeurIPS 2018 AI for Social Good workshop, 2018
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery
M Deudon, A Kalaitzis, I Goytom, MR Arefin, Z Lin, K Sankaran, ...
arXiv preprint arXiv:2002.06460, 2020
Flexible sampling of discrete data correlations without the marginal distributions
A Kalaitzis, R Silva
Advances in Neural Information Processing Systems 26, 2517-2525, 2013
Predicting gaming related properties from twitter profiles
A Kalaitzis, MI Gorinova, Y Lewenberg, Y Bachrach, M Fagan, D Carignan, ...
2016 IEEE Second International Conference on Big Data Computing Service and …, 2016
Image inpainting with Gaussian processes
A Kalaitzis
Master of Science Thesis, School of Informatics, University of Edinburgh, 2009
gptk: Gaussian processes tool-kit
A Kalaitzis, A Honkela, P Gao, ND Lawrence
URL http://CRAN. R-project. org/package= gptk, R package version 1, 2013
Bayesian inference via projections
R Silva, A Kalaitzis
Statistics and Computing 25 (4), 739-753, 2015
Online joint classification and anomaly detection via sparse coding
A Kalaitzis, JDB Nelson
2014 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2014
Prediction of GNSS Phase Scintillations: A Machine Learning Approach
K Lamb, G Malhotra, A Vlontzos, E Wagstaff, AG Baydin, A Bhiwandiwalla, ...
arXiv preprint arXiv:1910.01570, 2019
Learning with structured covariance matrices in linear Gaussian models
A Kalaitzis
University of Sheffield, 2013
Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent Networks
MR Arefin, V Michalski, PL St-Charles, A Kalaitzis, S Kim, SE Kahou, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
Correlation of Auroral Dynamics and GNSS Scintillation with an Autoencoder
AB Kara Lamb, Garima Malhotra, Athanasios Vlontzos, Edward Wagstaff, Atılım ...
arXiv preprint arXiv:1910.03085, 2019
Monte-Carlo methods for Computer Vision
A Kalaitzis
School of Informatics, University of Edinburgh, UK, 2009
RainBench: Towards Global Precipitation Forecasting from Satellite Imagery
CS de Witt, C Tong, V Zantedeschi, D De Martini, F Kalaitzis, M Chantry, ...
arXiv preprint arXiv:2012.09670, 2020
Super-resolution of Solar Magnetograms
PJ Wright, X Gitiaux, A Jungbluth, S Maloney, C Shneider, A Kalaitzis, ...
AGU Fall Meeting 2020, 2020
RainBench: Towards Global Precipitation Forecasting from Satellite Imagery
C Schroeder de Witt, C Tong, V Zantedeschi, D De Martini, F Kalaitzis, ...
arXiv e-prints, arXiv: 2012.09670, 2020
Pix2Streams: Dynamic Hydrology Maps from Satellite-LiDAR Fusion
D Garcia, G Mateo-Garcia, H Bernhardt, R Hagensieker, IGL Francos, ...
arXiv preprint arXiv:2011.07584, 2020
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