Articles with public access mandates - Theodoros (Theo) DamoulasLearn more
Available somewhere: 39
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with -Divergences
J Knoblauch, JE Jewson, T Damoulas
Advances in Neural Information Processing Systems 31, 2018
Mandates: UK Engineering and Physical Sciences Research Council
Data polygamy : the many-many relationships among urban spatio-temporal data sets
F Chirigati, H Doraiswamy, T Damoulas, J Freire
Proceedings of the 2016 ACM SIGMOD International Conference on Management of …, 2016
Mandates: US National Science Foundation
An optimization-centric view on Bayes' rule: Reviewing and generalizing variational inference
J Knoblauch, J Jewson, T Damoulas
Journal of Machine Learning Research 23 (132), 1-109, 2022
Mandates: UK Engineering and Physical Sciences Research Council, UK Research & Innovation
Spatio-temporal Bayesian on-line changepoint detection with model selection
J Knoblauch, T Damoulas
International Conference on Machine Learning, 2718-2727, 2018
Mandates: UK Engineering and Physical Sciences Research Council
Multi-resolution multi-task Gaussian processes
O Hamelijnck, T Damoulas, K Wang, M Girolami
Advances in Neural Information Processing Systems 32, 2019
Mandates: UK Engineering and Physical Sciences Research Council
Generalized variational inference
J Knoblauch, J Jewson, T Damoulas
stat 1050, 21, 2019
Mandates: UK Engineering and Physical Sciences Research Council
Exoplanet validation with machine learning: 50 new validated Kepler planets
DJ Armstrong, J Gamper, T Damoulas
Monthly Notices of the Royal Astronomical Society 504 (4), 5327-5344, 2021
Mandates: US National Aeronautics and Space Administration, UK Engineering and …
Distribution regression for sequential data
M Lemercier, C Salvi, T Damoulas, E Bonilla, T Lyons
International Conference on Artificial Intelligence and Statistics, 3754-3762, 2021
Mandates: UK Engineering and Physical Sciences Research Council, UK Research & Innovation
Transforming Gaussian processes with normalizing flows
J Maroñas, O Hamelijnck, J Knoblauch, T Damoulas
International Conference on Artificial Intelligence and Statistics, 1081-1089, 2021
Mandates: UK Engineering and Physical Sciences Research Council, UK Research & Innovation
Posterior inference for sparse hierarchical non-stationary models
K Monterrubio-Gómez, L Roininen, S Wade, T Damoulas, M Girolami
Computational Statistics & Data Analysis 148, 106954, 2020
Mandates: Academy of Finland, UK Engineering and Physical Sciences Research Council
Spatio-temporal variational Gaussian processes
O Hamelijnck, W Wilkinson, N Loppi, A Solin, T Damoulas
Advances in Neural Information Processing Systems 34, 23621-23633, 2021
Mandates: Academy of Finland, UK Engineering and Physical Sciences Research Council …
Robust Bayesian inference for simulator-based models via the MMD posterior bootstrap
C Dellaporta, J Knoblauch, T Damoulas, FX Briol
International Conference on Artificial Intelligence and Statistics, 943-970, 2022
Mandates: UK Engineering and Physical Sciences Research Council, UK Research & Innovation
Higher order kernel mean embeddings to capture filtrations of stochastic processes
C Salvi, M Lemercier, C Liu, B Horvath, T Damoulas, T Lyons
Advances in Neural Information Processing Systems 34, 16635-16647, 2021
Mandates: UK Engineering and Physical Sciences Research Council, UK Research & Innovation
Uncertainty-aware deep learning methods for robust diabetic retinopathy classification
J Jaskari, J Sahlsten, T Damoulas, J Knoblauch, S Särkkä, L Kärkkäinen, ...
IEEE Access 10, 76669-76681, 2022
Mandates: Academy of Finland
Dynamic causal Bayesian optimization
V Aglietti, N Dhir, J González, T Damoulas
Advances in Neural Information Processing Systems 34, 10549-10560, 2021
Mandates: UK Engineering and Physical Sciences Research Council, UK Research & Innovation
Can we assess mental health through social media and smart devices? Addressing bias in methodology and evaluation
A Tsakalidis, M Liakata, T Damoulas, AI Cristea
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019
Mandates: UK Engineering and Physical Sciences Research Council
Road distance and travel time for an improved house price Kriging predictor
H Crosby, T Damoulas, A Caton, P Davis, J Porto de Albuquerque, ...
Geo-Spatial Information Science 21 (3), 185-194, 2018
Mandates: UK Engineering and Physical Sciences Research Council
A Spatio-Temporal, Gaussian Process Regression, Real-Estate Price Predictor
H Crosby, P Davis, T Damoulas, S Jarvis
24th ACM SIGSPATIAL International Conference on Advances in Geographic …, 2016
Mandates: UK Engineering and Physical Sciences Research Council
Multi-task causal learning with gaussian processes
V Aglietti, T Damoulas, M Álvarez, J González
Advances in neural information processing systems 33, 6293-6304, 2020
Mandates: UK Engineering and Physical Sciences Research Council
Siggpde: Scaling sparse gaussian processes on sequential data
M Lemercier, C Salvi, T Cass, EV Bonilla, T Damoulas, TJ Lyons
International Conference on Machine Learning, 6233-6242, 2021
Mandates: UK Engineering and Physical Sciences Research Council, UK Research & Innovation
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