Theodoros Damoulas

According to our database, Theodoros Damoulas authored at least 70 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Near Real-Time Social Distance Estimation In London.

James Walsh, Oluwafunmilola Kesa, Andrew Wang, Mihai Ilas, Patrick O'Hara, Oscar Giles, Neil Dhir, Mark Girolami, Theodoros Damoulas

Comput. J., January, 2024

2023

Interventionally Consistent Surrogates for Agent-based Simulators.

Joel Dyer, Nicholas Bishop, Yorgos Felekis, Fabio Massimo Zennaro, Anisoara Calinescu, Theodoros Damoulas, Michael J. Wooldridge

CoRR, 2023

Causal Optimal Transport of Abstractions.

Yorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas

CoRR, 2023

Quantifying Consistency and Information Loss for Causal Abstraction Learning.

Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions.

Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, Widanalage Dhammika Widanage, Theodoros Damoulas

Proceedings of the Conference on Causal Learning and Reasoning, 2023

Causal Entropy Optimization.

Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference.

Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas

J. Mach. Learn. Res., 2022

Towards Computing an Optimal Abstraction for Structural Causal Models.

Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas

CoRR, 2022

Uncertainty-Aware Deep Learning Methods for Robust Diabetic Retinopathy Classification.

Joel Jaskari, Jaakko Sahlsten, Theodoros Damoulas, Jeremias Knoblauch, Simo Särkkä, Leo Kärkkäinen, Kustaa Hietala, Kimmo K. Kaski

IEEE Access, 2022

Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap.

Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities.

Shanaka Perera, Virginia Aglietti, Theodoros Damoulas

CoRR, 2021

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes.

Cristopher Salvi, Maud Lemercier, Chong Liu, Blanka Horvath, Theodoros Damoulas, Terry J. Lyons

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Spatio-Temporal Variational Gaussian Processes.

Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Dynamic Causal Bayesian Optimization.

Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data.

Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J. Lyons

Proceedings of the 38th International Conference on Machine Learning, 2021

Transforming Gaussian Processes With Normalizing Flows.

Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Distribution Regression for Sequential Data.

Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V. Bonilla, Terry J. Lyons

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Probabilistic Sequential Matrix Factorization.

Ömer Deniz Akyildiz, Gerrit J. J. van den Burg, Theodoros Damoulas, Mark F. J. Steel

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Road and travel time cross-validation for urban modelling.

Henry Crosby, Theodoros Damoulas, Stephen A. Jarvis

Int. J. Geogr. Inf. Sci., 2020

Posterior inference for sparse hierarchical non-stationary models.

Karla Monterrubio-Gómez, Lassi Roininen, Sara Wade, Theodoros Damoulas, Mark Girolami

Comput. Stat. Data Anal., 2020

Near Real-Time Social Distancing in London.

James Walsh, Oluwafunmilola Kesa, Andrew Wang, Mihai Ilas, Patrick O'Hara, Oscar Giles, Neil Dhir, Theodoros Damoulas

CoRR, 2020

An Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System.

Chance Haycock, Edward Thorpe-Woods, James Walsh, Patrick O'Hara, Oscar Giles, Neil Dhir, Theodoros Damoulas

CoRR, 2020

Exoplanet Validation with Machine Learning: 50 new validated Kepler planets.

David J. Armstrong, Jevgenij Gamper, Theodoros Damoulas

CoRR, 2020

Variational Autoencoding of PDE Inverse Problems.

Daniel J. Tait, Theodoros Damoulas

CoRR, 2020

Distribution Regression for Continuous-Time Processes via the Expected Signature.

Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V. Bonilla, Terry J. Lyons

CoRR, 2020

Generalized Bayesian Filtering via Sequential Monte Carlo.

Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen

CoRR, 2020

Bi-directional online transfer learning: a framework.

Helen McKay, Nathan Griffiths, Phillip Taylor, Theo Damoulas, Zhou Xu

Ann. des Télécommunications, 2020

Generalised Bayesian Filtering via Sequential Monte Carlo.

Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Multi-task Causal Learning with Gaussian Processes.

Virginia Aglietti, Theodoros Damoulas, Mauricio A. Álvarez, Javier González

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Non-separable Non-stationary random fields.

Kangrui Wang, Oliver Hamelijnck, Theodoros Damoulas, Mark F. J. Steel

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Embedding road networks and travel time into distance metrics for urban modelling.

Henry Crosby, Theodoros Damoulas, Stephen A. Jarvis

Int. J. Geogr. Inf. Sci., 2019

Probabilistic sequential matrix factorization.

Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel

CoRR, 2019

Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization.

Ying Zhang, Ömer Deniz Akyildiz, Theo Damoulas, Sotirios Sabanis

CoRR, 2019

On the Constrained Least-cost Tour Problem.

Patrick O'Hara, M. S. Ramanujan, Theodoros Damoulas

CoRR, 2019

Generalized Variational Inference.

Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas

CoRR, 2019

Multi-resolution Multi-task Gaussian Processes.

Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Structured Variational Inference in Continuous Cox Process Models.

Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Online Transfer Learning for Concept Drifting Data Streams.

Helen McKay, Nathan Griffiths, Phillip Taylor, Theo Damoulas, Zhou Xu

Proceedings of the 8th International Workshop on Big Data, 2019

Efficient Inference in Multi-task Cox Process Models.

Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Road distance and travel time for an improved house price Kriging predictor.

Henry Crosby, Theo Damoulas, Alex Caton, Paul Davis, João Porto de Albuquerque, Stephen A. Jarvis

Geo spatial Inf. Sci., 2018

Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences.

Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas

CoRR, 2018

Log Gaussian Cox Process Networks.

Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla

CoRR, 2018

Can We Assess Mental Health Through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation.

Adam Tsakalidis, Maria Liakata, Theo Damoulas, Alexandra I. Cristea

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences.

Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection.

Jeremias Knoblauch, Theodoros Damoulas

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Enabling Dependability-Driven Resource Use and Message Log-Analysis for Cluster System Diagnosis.

Edward Chuah, Arshad Jhumka, Samantha Alt, Theodoros Damoulas, Nentawe Gurumdimma, Marie-Christine Sawley, William L. Barth, Tommy Minyard, James C. Browne

Proceedings of the 24th IEEE International Conference on High Performance Computing, 2017

2016

Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets.

Fernando Chirigati, Harish Doraiswamy, Theodoros Damoulas, Juliana Freire

Proceedings of the 2016 International Conference on Management of Data, 2016

A spatio-temporal, Gaussian process regression, real-estate price predictor.

Henry Crosby, Paul Davis, Theodoros Damoulas, Stephen A. Jarvis

Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31, 2016

Combining Heterogeneous User Generated Data to Sense Well-being.

Adam Tsakalidis, Maria Liakata, Theodoros Damoulas, Brigitte Jellinek, Weisi Guo, Alexandra I. Cristea

Proceedings of the COLING 2016, 2016

2015

Reports from the 2015 AAAI Workshop Program.

Stefano V. Albrecht, J. Christopher Beck, David L. Buckeridge, Adi Botea, Cornelia Caragea, Chi-Hung Chi, Theodoros Damoulas, Bistra Dilkina, Eric Eaton, Pooyan Fazli, Sam Ganzfried, Marius Lindauer, Marlos C. Machado, Yuri Malitsky, Gary Marcus, Sebastiaan A. Meijer, Francesca Rossi, Arash Shaban-Nejad, Sylvie Thiébaux, Manuela M. Veloso, Toby Walsh, Can Wang, Jie Zhang, Yu Zheng

AI Mag., 2015

Learning Large-Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa.

Stefano Ermon, Yexiang Xue, Russell Toth, Bistra Dilkina, Richard Bernstein, Theodoros Damoulas, Patrick E. Clark, Steve DeGloria, Andrew Mude, Christopher Barrett, Carla P. Gomes

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Mining 911 Calls in New York City: Temporal Patterns, Detection, and Forecasting.

Alex Chohlas-Wood, Aliya Merali, Warren Reed, Theodoros Damoulas

Proceedings of the Artificial Intelligence for Cities, 2015

2014

Using Topological Analysis to Support Event-Guided Exploration in Urban Data.

Harish Doraiswamy, Nivan Ferreira, Theodoros Damoulas, Juliana Freire, Cláudio T. Silva

IEEE Trans. Vis. Comput. Graph., 2014

Crowdsourcing Meets Ecology: Hemisphere-Wide Spatiotemporal Species Distribution Models.

Daniel Fink, Theodoros Damoulas, Nicholas E. Bruns, Frank A. La Sorte, Wesley M. Hochachka, Carla P. Gomes, Steve Kelling

AI Mag., 2014

String Kernels for Complex Time-Series: Counting Targets from Sensed Movement.

Theodoros Damoulas, Jin He, Richard Bernstein, Carla P. Gomes, Anish Arora

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

2013

A Human/Computer Learning Network to Improve Biodiversity Conservation and Research.

Steve Kelling, Jeff Gerbracht, Daniel Fink, Carl Lagoze, Weng-Keen Wong, Jun Yu, Theodoros Damoulas, Carla P. Gomes

AI Mag., 2013

Improving Your Chances: Boosting Citizen Science Discovery.

Yexiang Xue, Bistra Dilkina, Theodoros Damoulas, Daniel Fink, Carla P. Gomes, Steve Kelling

Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, 2013

Adaptive Spatio-Temporal Exploratory Models: Hemisphere-wide species distributions from massively crowdsourced eBird data.

Daniel Fink, Theodoros Damoulas, Jaimin Dave

Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012

eBird: A Human/Computer Learning Network for Biodiversity Conservation and Research.

Steve Kelling, Jeff Gerbracht, Daniel Fink, Carl Lagoze, Weng-Keen Wong, Jun Yu, Theodoros Damoulas, Carla P. Gomes

Proceedings of the Twenty-Fourth Conference on Innovative Applications of Artificial Intelligence, 2012

2011

Protein interaction sentence detection using multiple semantic kernels.

Tamara Polajnar, Theodoros Damoulas, Mark A. Girolami

J. Biomed. Semant., 2011

Constraint Reasoning and Kernel Clustering for Pattern Decomposition with Scaling.

Ronan LeBras, Theodoros Damoulas, John M. Gregoire, Ashish Sabharwal, Carla P. Gomes, R. Bruce van Dover

Proceedings of the Principles and Practice of Constraint Programming - CP 2011, 2011

2010

Multiclass relevance vector machines: sparsity and accuracy.

Ioannis Psorakis, Theodoros Damoulas, Mark A. Girolami

IEEE Trans. Neural Networks, 2010

Bayesian Classification of Flight Calls with a Novel Dynamic Time Warping Kernel.

Theodoros Damoulas, Samuel Henry, Andrew Farnsworth, Michael Lanzone, Carla P. Gomes

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

2009

Probabilistic multiple kernel learning.

Theodoros Damoulas

PhD thesis, 2009

Pattern recognition with a Bayesian kernel combination machine.

Theodoros Damoulas, Mark A. Girolami

Pattern Recognit. Lett., 2009

Combining feature spaces for classification.

Theodoros Damoulas, Mark A. Girolami

Pattern Recognit., 2009

Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm.

Yiming Ying, Colin Campbell, Theodoros Damoulas, Mark A. Girolami

Proceedings of the Pattern Recognition in Bioinformatics, 2009

2008

Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection.

Theodoros Damoulas, Mark A. Girolami

Bioinform., 2008

Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins.

Theodoros Damoulas, Yiming Ying, Mark A. Girolami, Colin Campbell

Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

2005

Valency for Adaptive Homeostatic Agents: Relating Evolution and Learning.

Theodoros Damoulas, Ignasi Cos-Aguilera, Gillian M. Hayes, Tim Taylor

Proceedings of the Advances in Artificial Life, 8th European Conference, 2005