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ORCIDTheodoros Damoulas
Theo Damoulas
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2020 – today
- 2024
[j16]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): 95-109 (2024)- [c38]Patrick O'Hara, Ramanujan Sridharan, Theo Damoulas:
Routing on Sparse Graphs with Non-metric Costs for the Prize-collecting Travelling Salesperson Problem. ATT@ECAI 2024: 108-121 - [c37]Yorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas:
Causal Optimal Transport of Abstractions. CLeaR 2024: 462-498 - [i38]Fabio Massimo Zennaro, Nicholas Bishop, Joel Dyer, Yorgos Felekis, Anisoara Calinescu, Michael J. Wooldridge, Theodoros Damoulas:
Causally Abstracted Multi-armed Bandits. CoRR abs/2404.17493 (2024) - [i37]Charita Dellaporta, Patrick O'Hara, Theodoros Damoulas:
Distributionally Robust Optimisation with Bayesian Ambiguity Sets. CoRR abs/2409.03492 (2024) - [i36]Oliver Hamelijnck, Arno Solin, Theodoros Damoulas:
Physics-Informed Variational State-Space Gaussian Processes. CoRR abs/2409.13876 (2024) - [i35]Ioannis Zachos, Mark Girolami, Theodoros Damoulas:
Generating Origin-Destination Matrices in Neural Spatial Interaction Models. CoRR abs/2410.07352 (2024) - [i34]Patrick O'Hara, M. S. Ramanujan, Theodoros Damoulas:
Routing on Sparse Graphs with Non-metric Costs for the Prize-collecting Travelling Salesperson Problem. CoRR abs/2410.10440 (2024) - 2023
- [c36]Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas:
Causal Entropy Optimization. AISTATS 2023: 8586-8605 - [c35]Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, Widanalage Dhammika Widanage, Theodoros Damoulas:
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions. CLeaR 2023: 88-121 - [c34]Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas:
Quantifying Consistency and Information Loss for Causal Abstraction Learning. IJCAI 2023: 5750-5757 - [i33]Fabio Massimo Zennaro, Máté Drávucz, Geanina Apachitei, Widanalage Dhammika Widanage, Theodoros Damoulas:
Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions. CoRR abs/2301.05893 (2023) - [i32]Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas:
Quantifying Consistency and Information Loss for Causal Abstraction Learning. CoRR abs/2305.04357 (2023) - [i31]Yorgos Felekis, Fabio Massimo Zennaro, Nicola Branchini, Theodoros Damoulas:
Causal Optimal Transport of Abstractions. CoRR abs/2312.08107 (2023) - [i30]Joel Dyer, Nicholas Bishop, Yorgos Felekis, Fabio Massimo Zennaro, Anisoara Calinescu, Theodoros Damoulas, Michael J. Wooldridge:
Interventionally Consistent Surrogates for Agent-based Simulators. CoRR abs/2312.11158 (2023) - 2022
- [j15]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: 76669-76681 (2022) - [j14]Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference. J. Mach. Learn. Res. 23: 132:1-132:109 (2022) - [c33]Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol:
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. AISTATS 2022: 943-970 - [i29]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 abs/2201.09042 (2022) - [i28]Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol:
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. CoRR abs/2202.04744 (2022) - [i27]Fabio Massimo Zennaro, Paolo Turrini, Theodoros Damoulas:
Towards Computing an Optimal Abstraction for Structural Causal Models. CoRR abs/2208.00894 (2022) - [i26]Nicola Branchini, Virginia Aglietti, Neil Dhir, Theodoros Damoulas:
Causal Entropy Optimization. CoRR abs/2208.10981 (2022) - 2021
- [c32]Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas:
Transforming Gaussian Processes With Normalizing Flows. AISTATS 2021: 1081-1089 - [c31]Ömer Deniz Akyildiz, Gerrit J. J. van den Burg, Theodoros Damoulas, Mark F. J. Steel:
Probabilistic Sequential Matrix Factorization. AISTATS 2021: 3484-3492 - [c30]Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V. Bonilla, Terry J. Lyons:
Distribution Regression for Sequential Data. AISTATS 2021: 3754-3762 - [c29]Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J. Lyons:
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data. ICML 2021: 6233-6242 - [c28]Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas:
Dynamic Causal Bayesian Optimization. NeurIPS 2021: 10549-10560 - [c27]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: 16635-16647 - [c26]Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas:
Spatio-Temporal Variational Gaussian Processes. NeurIPS 2021: 23621-23633 - [i25]Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V. Bonilla, Theodoros Damoulas, Terry J. Lyons:
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data. CoRR abs/2105.04211 (2021) - [i24]Shanaka Perera, Virginia Aglietti, Theodoros Damoulas:
A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities. CoRR abs/2108.02594 (2021) - [i23]Cristopher Salvi, Maud Lemercier, Chong Liu, Blanka Horvath, Theodoros Damoulas, Terry J. Lyons:
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes. CoRR abs/2109.03582 (2021) - [i22]Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas:
Dynamic Causal Bayesian Optimization. CoRR abs/2110.13891 (2021) - [i21]Oliver Hamelijnck, William J. Wilkinson, Niki A. Loppi, Arno Solin, Theodoros Damoulas:
Spatio-Temporal Variational Gaussian Processes. CoRR abs/2111.01732 (2021) - 2020
- [j13]Helen McKay, Nathan Griffiths, Phillip Taylor, Theo Damoulas, Zhou Xu:
Bi-directional online transfer learning: a framework. Ann. des Télécommunications 75(9-10): 523-547 (2020) - [j12]Karla Monterrubio-Gómez, Lassi Roininen, Sara Wade, Theodoros Damoulas, Mark Girolami:
Posterior inference for sparse hierarchical non-stationary models. Comput. Stat. Data Anal. 148: 106954 (2020) - [j11]Henry Crosby, Theodoros Damoulas, Stephen A. Jarvis:
Road and travel time cross-validation for urban modelling. Int. J. Geogr. Inf. Sci. 34(1): 98-118 (2020) - [c25]Kangrui Wang, Oliver Hamelijnck, Theodoros Damoulas, Mark F. J. Steel:
Non-separable Non-stationary random fields. ICML 2020: 9887-9897 - [c24]Virginia Aglietti, Theodoros Damoulas, Mauricio A. Álvarez, Javier González:
Multi-task Causal Learning with Gaussian Processes. NeurIPS 2020 - [c23]Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen:
Generalised Bayesian Filtering via Sequential Monte Carlo. NeurIPS 2020 - [i20]Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen:
Generalized Bayesian Filtering via Sequential Monte Carlo. CoRR abs/2002.09998 (2020) - [i19]Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V. Bonilla, Terry J. Lyons:
Distribution Regression for Continuous-Time Processes via the Expected Signature. CoRR abs/2006.05805 (2020) - [i18]Daniel J. Tait, Theodoros Damoulas:
Variational Autoencoding of PDE Inverse Problems. CoRR abs/2006.15641 (2020) - [i17]David J. Armstrong, Jevgenij Gamper, Theodoros Damoulas:
Exoplanet Validation with Machine Learning: 50 new validated Kepler planets. CoRR abs/2008.10516 (2020) - [i16]Virginia Aglietti, Theodoros Damoulas, Mauricio A. Álvarez, Javier González:
Multi-task Causal Learning with Gaussian Processes. CoRR abs/2009.12821 (2020) - [i15]Juan Maroñas, Oliver Hamelijnck, Jeremias Knoblauch, Theodoros Damoulas:
Transforming Gaussian Processes With Normalizing Flows. CoRR abs/2011.01596 (2020) - [i14]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 abs/2012.07574 (2020) - [i13]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 abs/2012.07751 (2020)
2010 – 2019
- 2019
- [j10]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): 512-536 (2019) - [c22]Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla:
Efficient Inference in Multi-task Cox Process Models. AISTATS 2019: 537-546 - [c21]Helen McKay, Nathan Griffiths, Phillip Taylor, Theo Damoulas, Zhou Xu:
Online Transfer Learning for Concept Drifting Data Streams. BigMine@KDD 2019 - [c20]Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps:
Structured Variational Inference in Continuous Cox Process Models. NeurIPS 2019: 12437-12447 - [c19]Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami:
Multi-resolution Multi-task Gaussian Processes. NeurIPS 2019: 14025-14035 - [i12]Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
Generalized Variational Inference. CoRR abs/1904.02063 (2019) - [i11]Virginia Aglietti, Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps:
Structured Variational Inference in Continuous Cox Process Models. CoRR abs/1906.03161 (2019) - [i10]Patrick O'Hara, M. S. Ramanujan, Theodoros Damoulas:
On the Constrained Least-cost Tour Problem. CoRR abs/1906.07754 (2019) - [i9]Oliver Hamelijnck, Theodoros Damoulas, Kangrui Wang, Mark A. Girolami:
Multi-resolution Multi-task Gaussian Processes. CoRR abs/1906.08344 (2019) - [i8]Ying Zhang, Ömer Deniz Akyildiz, Theo Damoulas, Sotirios Sabanis:
Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization. CoRR abs/1910.02008 (2019) - [i7]Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel:
Probabilistic sequential matrix factorization. CoRR abs/1910.03906 (2019) - 2018
- [j9]Henry Crosby, Theo Damoulas, Alex Caton, Paul Davis, João Porto de Albuquerque, Stephen A. Jarvis:
Road distance and travel time for an improved house price Kriging predictor. Geo spatial Inf. Sci. 21(3): 185-194 (2018) - [c18]Jeremias Knoblauch, Theodoros Damoulas:
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection. ICML 2018: 2723-2732 - [c17]Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences. NeurIPS 2018: 64-75 - [c16]Adam Tsakalidis, Maria Liakata, Theo Damoulas, Alexandra I. Cristea:
Can We Assess Mental Health Through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation. ECML/PKDD (3) 2018: 407-423 - [i6]Jeremias Knoblauch, Theodoros Damoulas:
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection. CoRR abs/1805.05383 (2018) - [i5]Virginia Aglietti, Theodoros Damoulas, Edwin V. Bonilla:
Log Gaussian Cox Process Networks. CoRR abs/1805.09781 (2018) - [i4]Jeremias Knoblauch, Jack Jewson, Theodoros Damoulas:
Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences. CoRR abs/1806.02261 (2018) - [i3]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 abs/1807.07351 (2018) - 2017
- [c15]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: 317-327 - 2016
- [c14]Adam Tsakalidis, Maria Liakata, Theodoros Damoulas, Brigitte Jellinek, Weisi Guo, Alexandra I. Cristea:
Combining Heterogeneous User Generated Data to Sense Well-being. COLING 2016: 3007-3018 - [c13]Henry Crosby, Paul Davis, Theodoros Damoulas, Stephen A. Jarvis:
A spatio-temporal, Gaussian process regression, real-estate price predictor. SIGSPATIAL/GIS 2016: 68:1-68:4 - [c12]Fernando Chirigati, Harish Doraiswamy, Theodoros Damoulas, Juliana Freire:
Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets. SIGMOD Conference 2016: 1011-1025 - [i2]Fernando Chirigati, Harish Doraiswamy, Theodoros Damoulas, Juliana Freire:
Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets. CoRR abs/1610.06978 (2016) - 2015
- [c11]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 - [c10]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: 644-650 - [e1]Theodoros Damoulas:
Artificial Intelligence for Cities, Papers from the 2015 AAAI Workshop, Austin, Texas, USA, January 25, 2015. AAAI Technical Report WS-15-04, AAAI Press 2015, ISBN 978-1-57735-715-5 [contents] - [i1]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): 90-101 (2015) - 2014
- [j8]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): 19-30 (2014) - [j7]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): 2634-2643 (2014) - [c9]Theodoros Damoulas, Jin He, Richard Bernstein, Carla P. Gomes, Anish Arora:
String Kernels for Complex Time-Series: Counting Targets from Sensed Movement. ICPR 2014: 4429-4434 - 2013
- [j6]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): 10-20 (2013) - [c8]Daniel Fink, Theodoros Damoulas, Jaimin Dave:
Adaptive Spatio-Temporal Exploratory Models: Hemisphere-wide species distributions from massively crowdsourced eBird data. AAAI 2013: 1284-1290 - [c7]Yexiang Xue, Bistra Dilkina, Theodoros Damoulas, Daniel Fink, Carla P. Gomes, Steve Kelling:
Improving Your Chances: Boosting Citizen Science Discovery. HCOMP 2013: 198-206 - 2012
- [c6]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: 2229-2236 - 2011
- [j5]Tamara Polajnar, Theodoros Damoulas, Mark A. Girolami:
Protein interaction sentence detection using multiple semantic kernels. J. Biomed. Semant. 2: 1 (2011) - [c5]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: 508-522 - 2010
- [j4]Ioannis Psorakis, Theodoros Damoulas, Mark A. Girolami:
Multiclass relevance vector machines: sparsity and accuracy. IEEE Trans. Neural Networks 21(10): 1588-1598 (2010) - [c4]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: 424-429
2000 – 2009
- 2009
- [b1]Theodoros Damoulas:
Probabilistic multiple kernel learning. University of Glasgow, UK, 2009 - [j3]Theodoros Damoulas, Mark A. Girolami:
Combining feature spaces for classification. Pattern Recognit. 42(11): 2671-2683 (2009) - [j2]Theodoros Damoulas, Mark A. Girolami:
Pattern recognition with a Bayesian kernel combination machine. Pattern Recognit. Lett. 30(1): 46-54 (2009) - [c3]Yiming Ying, Colin Campbell, Theodoros Damoulas, Mark A. Girolami:
Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm. PRIB 2009: 427-438 - 2008
- [j1]Theodoros Damoulas, Mark A. Girolami:
Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection. Bioinform. 24(10): 1264-1270 (2008) - [c2]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: 577-582 - 2005
- [c1]Theodoros Damoulas, Ignasi Cos-Aguilera, Gillian M. Hayes, Tim Taylor:
Valency for Adaptive Homeostatic Agents: Relating Evolution and Learning. ECAL 2005: 936-945
Coauthor Index
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