Theodoros Damoulas

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 65

Top Venues

CoRR

NeurIPS

AISTATS

ICML

University of Glasgow, UK (PHD)

Education History

University of Glasgow, UK

PHD

Publications

Fabio Massimo Zennaro, Nicholas Bishop, Joel Dyer, Yorgos Felekis, Anisoara Calinescu, Michael J. Wooldridge, Theodoros Damoulas
Causally Abstracted Multi-armed Bandits. CoRR (2024)
James Walsh, Oluwafunmilola Kesa, Andrew Wang, Mihai Ilas, Patrick O'Hara, Oscar Giles, Neil Dhir, Mark Girolami, Theodoros Damoulas
Near Real-Time Social Distance Estimation In London. Comput. J. 67 (1) (2024)
Yorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas
Causal Optimal Transport of Abstractions. CLeaR (2024)
Joel Dyer, Nicholas Bishop, Yorgos Felekis, Fabio Massimo Zennaro, Anisoara Calinescu, Theodoros Damoulas, Michael Wooldridge
Interventionally Consistent Surrogates for Agent-based Simulators. CoRR (2023)
Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, Widanalage Dhammika Widanage, Theodoros Damoulas
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions. CoRR (2023)
Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas
Quantifying Consistency and Information Loss for Causal Abstraction Learning. CoRR (2023)
Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas
Causal Entropy Optimization. AISTATS (2023)
Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas
Quantifying Consistency and Information Loss for Causal Abstraction Learning. IJCAI (2023)
Yorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas
Causal Optimal Transport of Abstractions. CoRR (2023)
Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, Widanalage Dhammika Widanage, Theodoros Damoulas
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions. CLeaR (2023)
Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas
Causal Entropy Optimization. CoRR (2022)
Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. AISTATS (2022)
Joel Jaskari, Jaakko Sahlsten, Theodoros Damoulas, Jeremias Knoblauch, Simo Särkkä, Leo Kärkkäinen, Kustaa Hietala, Kimmo Kaski
Uncertainty-aware deep learning methods for robust diabetic retinopathy classification. CoRR (2022)
Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. CoRR (2022)
Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas
An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference. J. Mach. Learn. Res. 23 (2022)
Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas
Towards Computing an Optimal Abstraction for Structural Causal Models. CoRR (2022)
Joel Jaskari, Jaakko Sahlsten, Theodoros Damoulas, Jeremias Knoblauch, Simo Särkkä, Leo Kärkkäinen, Kustaa Hietala, Kimmo K. Kaski
Uncertainty-Aware Deep Learning Methods for Robust Diabetic Retinopathy Classification. IEEE Access 10 (2022)
Cristopher Salvi, Maud Lemercier, Chong Liu, Blanka Hovarth, Theodoros Damoulas, Terry J. Lyons
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes. CoRR (2021)
Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas
Dynamic Causal Bayesian Optimization. NeurIPS (2021)
Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas
Spatio-Temporal Variational Gaussian Processes. CoRR (2021)
Ömer Deniz Akyildiz, Gerrit van den Burg, Theodoros Damoulas, Mark F. J. Steel
Probabilistic Sequential Matrix Factorization. AISTATS (2021)
Cristopher Salvi, Maud Lemercier, Chong Liu, Blanka Horvath, Theodoros Damoulas, Terry J. Lyons
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes. NeurIPS (2021)
Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J. Lyons
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data. ICML (2021)
Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J. Lyons
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data. CoRR (2021)
Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas
Spatio-Temporal Variational Gaussian Processes. NeurIPS (2021)
Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas
Transforming Gaussian Processes With Normalizing Flows. AISTATS (2021)
Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas
Dynamic Causal Bayesian Optimization. CoRR (2021)
Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V. Bonilla, Terry J. Lyons
Distribution Regression for Sequential Data. AISTATS (2021)
Shanaka Perera, Virginia Aglietti, Theodoros Damoulas
A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities. CoRR (2021)
Henry Crosby, Theodoros Damoulas, Stephen A. Jarvis
Road and travel time cross-validation for urban modelling. Int. J. Geogr. Inf. Sci. 34 (1) (2020)
Kangrui Wang, Oliver Hamelijnck, Theodoros Damoulas, Mark F. J. Steel
Non-separable Non-stationary random fields. ICML (2020)
Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen
Generalised Bayesian Filtering via Sequential Monte Carlo. NeurIPS (2020)
Virginia Aglietti, Theodoros Damoulas, Mauricio Álvarez, Javier González
Multi-task Causal Learning with Gaussian Processes. CoRR (2020)
Chance Haycock, Edward Thorpe-Woods, James Walsh, Patrick O'Hara, Oscar Giles, Neil Dhir, Theodoros Damoulas
An Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System. CoRR (2020)
Karla Monterrubio-Gómez, Lassi Roininen, Sara Wade, Theodoros Damoulas, Mark Girolami
Posterior inference for sparse hierarchical non-stationary models. Comput. Stat. Data Anal. 148 (2020)
Virginia Aglietti, Theodoros Damoulas, Mauricio Álvarez, Javier Gonzalez
Multi-task Causal Learning with Gaussian Processes. NeurIPS (2020)
David J. Armstrong, Jevgenij Gamper, Theodoros Damoulas
Exoplanet Validation with Machine Learning: 50 new validated Kepler planets. CoRR (2020)
Daniel J. Tait, Theodoros Damoulas
Variational Autoencoding of PDE Inverse Problems. CoRR (2020)
Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V. Bonilla, Terry J. Lyons
Distribution Regression for Continuous-Time Processes via the Expected Signature. CoRR (2020)
Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen
Generalized Bayesian Filtering via Sequential Monte Carlo. CoRR (2020)
James Walsh, Oluwafunmilola Kesa, Andrew Wang, Mihai Ilas, Patrick O'Hara, Oscar Giles, Neil Dhir, Theodoros Damoulas
Near Real-Time Social Distancing in London. CoRR (2020)
Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas
Transforming Gaussian Processes With Normalizing Flows. CoRR (2020)
Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla
Efficient Inference in Multi-task Cox Process Models. AISTATS (2019)
Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami
Multi-resolution Multi-task Gaussian Processes. CoRR (2019)
Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel
Probabilistic sequential matrix factorization. CoRR (2019)
Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps
Structured Variational Inference in Continuous Cox Process Models. CoRR (2019)
Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami
Multi-resolution Multi-task Gaussian Processes. NeurIPS (2019)
Patrick O'Hara, M. S. Ramanujan, Theodoros Damoulas
On the Constrained Least-cost Tour Problem. CoRR (2019)
Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas
Generalized Variational Inference. CoRR (2019)
Henry Crosby, Theodoros Damoulas, Stephen A. Jarvis
Embedding road networks and travel time into distance metrics for urban modelling. Int. J. Geogr. Inf. Sci. 33 (3) (2019)
Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps
Structured Variational Inference in Continuous Cox Process Models. NeurIPS (2019)
Adam Tsakalidis, Maria Liakata, Theodoros Damoulas, Alexandra I. Cristea
Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation. CoRR (2018)
Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla
Log Gaussian Cox Process Networks. CoRR (2018)
Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences. CoRR (2018)
Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences. NeurIPS (2018)
Jeremias Knoblauch, Theodoros Damoulas
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection. ICML (2018)
Jeremias Knoblauch, Theodoros Damoulas
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection. CoRR (2018)
Edward Chuah, Arshad Jhumka, Samantha Alt, Theodoros Damoulas, Nentawe Gurumdimma, Marie-Christine Sawley, William L. Barth, Tommy Minyard, James C. Browne
Enabling Dependability-Driven Resource Use and Message Log-Analysis for Cluster System Diagnosis. HiPC (2017)
Fernando Chirigati, Harish Doraiswamy, Theodoros Damoulas, Juliana Freire
Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets. CoRR (2016)
Henry Crosby, Paul Davis, Theodoros Damoulas, Stephen A. Jarvis
A spatio-temporal, Gaussian process regression, real-estate price predictor. SIGSPATIAL/GIS (2016)
Fernando Chirigati, Harish Doraiswamy, Theodoros Damoulas, Juliana Freire
Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets. SIGMOD Conference (2016)
Adam Tsakalidis, Maria Liakata, Theodoros Damoulas, Brigitte Jellinek, Weisi Guo, Alexandra I. Cristea
Combining Heterogeneous User Generated Data to Sense Well-being. COLING (2016)
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
Reports from the 2015 AAAI Workshop Program. AI Mag. 36 (2) (2015)
Alex Chohlas-Wood, Aliya Merali, Warren Reed, Theodoros Damoulas
Mining 911 Calls in New York City: Temporal Patterns, Detection, and Forecasting. AAAI Workshop: AI for Cities (2015)
Stefano Ermon, Yexiang Xue, Russell Toth, Bistra Dilkina, Richard Bernstein, Theodoros Damoulas, Patrick E. Clark, Steve DeGloria, Andrew Mude, Christopher Barrett, Carla P. Gomes
Learning Large-Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa. AAAI (2015)
Harish Doraiswamy, Nivan Ferreira, Theodoros Damoulas, Juliana Freire, Cláudio T. Silva
Using Topological Analysis to Support Event-Guided Exploration in Urban Data. IEEE Trans. Vis. Comput. Graph. 20 (12) (2014)
Daniel Fink, Theodoros Damoulas, Nicholas E. Bruns, Frank A. La Sorte, Wesley M. Hochachka, Carla P. Gomes, Steve Kelling
Crowdsourcing Meets Ecology: Hemisphere-Wide Spatiotemporal Species Distribution Models. AI Mag. 35 (2) (2014)
Theodoros Damoulas, Jin He, Richard Bernstein, Carla P. Gomes, Anish Arora
String Kernels for Complex Time-Series: Counting Targets from Sensed Movement. ICPR (2014)
Daniel Fink, Theodoros Damoulas, Jaimin Dave
Adaptive Spatio-Temporal Exploratory Models: Hemisphere-wide species distributions from massively crowdsourced eBird data. AAAI (2013)
Yexiang Xue, Bistra Dilkina, Theodoros Damoulas, Daniel Fink, Carla P. Gomes, Steve Kelling
Improving Your Chances: Boosting Citizen Science Discovery. HCOMP (2013)
Steve Kelling, Jeff Gerbracht, Daniel Fink, Carl Lagoze, Weng-Keen Wong, Jun Yu, Theodoros Damoulas, Carla P. Gomes
A Human/Computer Learning Network to Improve Biodiversity Conservation and Research. AI Mag. 34 (1) (2013)
Steve Kelling, Jeff Gerbracht, Daniel Fink, Carl Lagoze, Weng-Keen Wong, Jun Yu, Theodoros Damoulas, Carla P. Gomes
eBird: A Human/Computer Learning Network for Biodiversity Conservation and Research. IAAI (2012)
Ronan LeBras, Theodoros Damoulas, John M. Gregoire, Ashish Sabharwal, Carla P. Gomes, R. Bruce van Dover
Constraint Reasoning and Kernel Clustering for Pattern Decomposition with Scaling. CP (2011)
Tamara Polajnar, Theodoros Damoulas, Mark A. Girolami
Protein interaction sentence detection using multiple semantic kernels. J. Biomed. Semant. 2 (2011)
Ioannis Psorakis, Theodoros Damoulas, Mark A. Girolami
Multiclass relevance vector machines: sparsity and accuracy. IEEE Trans. Neural Networks 21 (10) (2010)
Theodoros Damoulas, Samuel Henry, Andrew Farnsworth, Michael Lanzone, Carla P. Gomes
Bayesian Classification of Flight Calls with a Novel Dynamic Time Warping Kernel. ICMLA (2010)
Theodoros Damoulas, Mark A. Girolami
Combining feature spaces for classification. Pattern Recognit. 42 (11) (2009)
Yiming Ying, Colin Campbell, Theodoros Damoulas, Mark A. Girolami
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm. PRIB (2009)
Theodoros Damoulas, Mark A. Girolami
Pattern recognition with a Bayesian kernel combination machine. Pattern Recognit. Lett. 30 (1) (2009)
Theodoros Damoulas, Yiming Ying, Mark A. Girolami, Colin Campbell
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins. ICMLA (2008)
Theodoros Damoulas, Mark A. Girolami
Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection. Bioinform. 24 (10) (2008)
Theodoros Damoulas, Ignasi Cos-Aguilera, Gillian M. Hayes, Tim Taylor
Valency for Adaptive Homeostatic Agents: Relating Evolution and Learning. ECAL (2005)

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Publication Activity (10 Years)

Top Topics

Top Venues

Theodoros Damoulas