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• 2025
• 
  [c44]
  Charita Dellaporta,Patrick O'Hara,Theodoros Damoulas:
  Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets.ICML2025
• 
  [c43]
  Terje Mildner,Oliver Hamelijnck,Paris Giampouras,Theodoros Damoulas:
  Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework.ICML2025
• 
  [i43]
  Terje Mildner,Oliver Hamelijnck,Paris Giampouras,Theodoros Damoulas:
  Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework.CoRRabs/2502.00846 (2025)
• 
  [i42]
  Charita Dellaporta,Patrick O'Hara,Theodoros Damoulas:
  Decision Making under Model Misspecification: DRO with Robust Bayesian Ambiguity Sets.CoRRabs/2505.03585 (2025)
• 
  [i41]
  David Huk,Theodoros Damoulas:
  Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies.CoRRabs/2509.19707 (2025)
• 
  [i40]
  Yorgos Felekis,Theodoros Damoulas,Paris Giampouras:
  Distributionally Robust Causal Abstractions.CoRRabs/2510.04842 (2025)
• 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)
• 
  [c42]
  Patrick O'Hara,Ramanujan Sridharan,Theo Damoulas:
  Routing on Sparse Graphs with Non-metric Costs for the Prize-collecting Travelling Salesperson Problem.ATT@ECAI2024:108-121
• 
  [c41]
  Yorgos Felekis,Fabio Massimo Zennaro,Nicola Branchini,Theodoros Damoulas:
  Causal Optimal Transport of Abstractions.CLeaR2024:462-498
• 
  [c40]
  Joel Dyer,Nicholas Bishop,Yorgos Felekis,Fabio Massimo Zennaro,Anisoara Calinescu,Theodoros Damoulas,Michael J. Wooldridge:
  Interventionally Consistent Surrogates for Complex Simulation Models.NeurIPS2024
• 
  [c39]
  Oliver Hamelijnck,Arno Solin,Theodoros Damoulas:
  Physics-Informed Variational State-Space Gaussian Processes.NeurIPS2024
• 
  [c38]
  Ioannis Zachos,Mark Girolami,Theodoros Damoulas:
  Generating Origin-Destination Matrices in Neural Spatial Interaction Models.NeurIPS2024
• 
  [c37]
  Fabio Massimo Zennaro,Nicholas Bishop,Joel Dyer,Yorgos Felekis,Anisoara Calinescu,Michael J. Wooldridge,Theodoros Damoulas:
  Causally Abstracted Multi-armed Bandits.UAI2024:4109-4139
• 
  [i39]
  Fabio Massimo Zennaro,Nicholas Bishop,Joel Dyer,Yorgos Felekis,Anisoara Calinescu,Michael J. Wooldridge,Theodoros Damoulas:
  Causally Abstracted Multi-armed Bandits.CoRRabs/2404.17493 (2024)
• 
  [i38]
  Charita Dellaporta,Patrick O'Hara,Theodoros Damoulas:
  Distributionally Robust Optimisation with Bayesian Ambiguity Sets.CoRRabs/2409.03492 (2024)
• 
  [i37]
  Oliver Hamelijnck,Arno Solin,Theodoros Damoulas:
  Physics-Informed Variational State-Space Gaussian Processes.CoRRabs/2409.13876 (2024)
• 
  [i36]
  Ioannis Zachos,Mark Girolami,Theodoros Damoulas:
  Generating Origin-Destination Matrices in Neural Spatial Interaction Models.CoRRabs/2410.07352 (2024)
• 
  [i35]
  Patrick O'Hara,M. S. Ramanujan,Theodoros Damoulas:
  Routing on Sparse Graphs with Non-metric Costs for the Prize-collecting Travelling Salesperson Problem.CoRRabs/2410.10440 (2024)
• 
  [i34]
  Charita Dellaporta,Patrick O'Hara,Theodoros Damoulas:
  Decision Making under the Exponential Family: Distributionally Robust Optimisation with Bayesian Ambiguity Sets.CoRRabs/2411.16829 (2024)
• 2023
• 
  [c36]
  Nicola Branchini,Virginia Aglietti,Neil Dhir,Theodoros Damoulas:
  Causal Entropy Optimization.AISTATS2023:8586-8605
• 
  [c35]
  Fabio Massimo Zennaro,Máté Drávucz,Geanina Apachitei,Widanalage Dhammika Widanage,Theodoros Damoulas:
  Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions.CLeaR2023:88-121
• 
  [c34]
  Fabio Massimo Zennaro,Paolo Turrini,Theodoros Damoulas:
  Quantifying Consistency and Information Loss for Causal Abstraction Learning.IJCAI2023:5750-5757
• 
  [i33]
  Fabio Massimo Zennaro,Máté Drávucz,Geanina Apachitei,Widanalage Dhammika Widanage,Theodoros Damoulas:
  Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions.CoRRabs/2301.05893 (2023)
• 
  [i32]
  Fabio Massimo Zennaro,Paolo Turrini,Theodoros Damoulas:
  Quantifying Consistency and Information Loss for Causal Abstraction Learning.CoRRabs/2305.04357 (2023)
• 
  [i31]
  Yorgos Felekis,Fabio Massimo Zennaro,Nicola Branchini,Theodoros Damoulas:
  Causal Optimal Transport of Abstractions.CoRRabs/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.CoRRabs/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 Access10:76669-76681 (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.AISTATS2022:943-970
• 
  [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.CoRRabs/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.CoRRabs/2202.04744 (2022)
• 
  [i27]
  Fabio Massimo Zennaro,Paolo Turrini,Theodoros Damoulas:
  Towards Computing an Optimal Abstraction for Structural Causal Models.CoRRabs/2208.00894 (2022)
• 
  [i26]
  Nicola Branchini,Virginia Aglietti,Neil Dhir,Theodoros Damoulas:
  Causal Entropy Optimization.CoRRabs/2208.10981 (2022)
• 2021
• 
  [c32]
  Juan Maroñas,Oliver Hamelijnck,Jeremias Knoblauch,Theodoros Damoulas:
  Transforming Gaussian Processes With Normalizing Flows.AISTATS2021:1081-1089
• 
  [c31]
  Ömer Deniz Akyildiz,Gerrit J. J. van den Burg,Theodoros Damoulas,Mark F. J. Steel:
  Probabilistic Sequential Matrix Factorization.AISTATS2021:3484-3492
• 
  [c30]
  Maud Lemercier,Cristopher Salvi,Theodoros Damoulas,Edwin V. Bonilla,Terry J. Lyons:
  Distribution Regression for Sequential Data.AISTATS2021:3754-3762
• 
  [c29]
  Maud Lemercier,Cristopher Salvi,Thomas Cass,Edwin V. Bonilla,Theodoros Damoulas,Terry J. Lyons:
  SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data.ICML2021:6233-6242
• 
  [c28]
  Virginia Aglietti,Neil Dhir,Javier González,Theodoros Damoulas:
  Dynamic Causal Bayesian Optimization.NeurIPS2021:10549-10560
• 
  [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.NeurIPS2021:16635-16647
• 
  [c26]
  Oliver Hamelijnck,William J. Wilkinson,Niki Andreas Lopi,Arno Solin,Theodoros Damoulas:
  Spatio-Temporal Variational Gaussian Processes.NeurIPS2021:23621-23633
• 
  [i25]
  Maud Lemercier,Cristopher Salvi,Thomas Cass,Edwin V. Bonilla,Theodoros Damoulas,Terry J. Lyons:
  SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data.CoRRabs/2105.04211 (2021)
• 
  [i24]
  Shanaka Perera,Virginia Aglietti,Theodoros Damoulas:
  A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities.CoRRabs/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.CoRRabs/2109.03582 (2021)
• 
  [i22]
  Virginia Aglietti,Neil Dhir,Javier González,Theodoros Damoulas:
  Dynamic Causal Bayesian Optimization.CoRRabs/2110.13891 (2021)
• 
  [i21]
  Oliver Hamelijnck,William J. Wilkinson,Niki Andreas Lopi,Arno Solin,Theodoros Damoulas:
  Spatio-Temporal Variational Gaussian Processes.CoRRabs/2111.01732 (2021)
• 2020
• 
  [j13]
  Helen McKay,Nathan Griffiths,Phillip Taylor,Theo Damoulas,Zhou Xu:
  Bi-directional online transfer learning: a framework.Ann. des Télécommunications75(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.ICML2020:9887-9897
• 
  [c24]
  Virginia Aglietti,Theodoros Damoulas,Mauricio A. Álvarez,Javier González:
  Multi-task Causal Learning with Gaussian Processes.NeurIPS2020
• 
  [c23]
  Ayman Boustati,Ömer Deniz Akyildiz,Theodoros Damoulas,Adam M. Johansen:
  Generalised Bayesian Filtering via Sequential Monte Carlo.NeurIPS2020
• 
  [i20]
  Ayman Boustati,Ömer Deniz Akyildiz,Theodoros Damoulas,Adam M. Johansen:
  Generalized Bayesian Filtering via Sequential Monte Carlo.CoRRabs/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.CoRRabs/2006.05805 (2020)
• 
  [i18]
  Daniel J. Tait,Theodoros Damoulas:
  Variational Autoencoding of PDE Inverse Problems.CoRRabs/2006.15641 (2020)
• 
  [i17]
  David J. Armstrong,Jevgenij Gamper,Theodoros Damoulas:
  Exoplanet Validation with Machine Learning: 50 new validated Kepler planets.CoRRabs/2008.10516 (2020)
• 
  [i16]
  Virginia Aglietti,Theodoros Damoulas,Mauricio A. Álvarez,Javier González:
  Multi-task Causal Learning with Gaussian Processes.CoRRabs/2009.12821 (2020)
• 
  [i15]
  Juan Maroñas,Oliver Hamelijnck,Jeremias Knoblauch,Theodoros Damoulas:
  Transforming Gaussian Processes With Normalizing Flows.CoRRabs/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.CoRRabs/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.CoRRabs/2012.07751 (2020)

• 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.AISTATS2019:537-546
• 
  [c21]
  Helen McKay,Nathan Griffiths,Phillip Taylor,Theo Damoulas,Zhou Xu:
  Online Transfer Learning for Concept Drifting Data Streams.BigMine@KDD2019
• 
  [c20]
  Virginia Aglietti,Edwin V. Bonilla,Theodoros Damoulas,Sally Cripps:
  Structured Variational Inference in Continuous Cox Process Models.NeurIPS2019:12437-12447
• 
  [c19]
  Oliver Hamelijnck,Theodoros Damoulas,Kangrui Wang,Mark A. Girolami:
  Multi-resolution Multi-task Gaussian Processes.NeurIPS2019:14025-14035
• 
  [i12]
  Jeremias Knoblauch,Jack Jewson,Theodoros Damoulas:
  Generalized Variational Inference.CoRRabs/1904.02063 (2019)
• 
  [i11]
  Virginia Aglietti,Edwin V. Bonilla,Theodoros Damoulas,Sally Cripps:
  Structured Variational Inference in Continuous Cox Process Models.CoRRabs/1906.03161 (2019)
• 
  [i10]
  Patrick O'Hara,M. S. Ramanujan,Theodoros Damoulas:
  On the Constrained Least-cost Tour Problem.CoRRabs/1906.07754 (2019)
• 
  [i9]
  Oliver Hamelijnck,Theodoros Damoulas,Kangrui Wang,Mark A. Girolami:
  Multi-resolution Multi-task Gaussian Processes.CoRRabs/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.CoRRabs/1910.02008 (2019)
• 
  [i7]
  Ömer Deniz Akyildiz,Theodoros Damoulas,Mark F. J. Steel:
  Probabilistic sequential matrix factorization.CoRRabs/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.ICML2018:2723-2732
• 
  [c17]
  Jeremias Knoblauch,Jack Jewson,Theodoros Damoulas:
  Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences.NeurIPS2018:64-75
• 
  [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.CoRRabs/1805.05383 (2018)
• 
  [i5]
  Virginia Aglietti,Theodoros Damoulas,Edwin V. Bonilla:
  Log Gaussian Cox Process Networks.CoRRabs/1805.09781 (2018)
• 
  [i4]
  Jeremias Knoblauch,Jack Jewson,Theodoros Damoulas:
  Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences.CoRRabs/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.CoRRabs/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.HiPC2017:317-327
• 2016
• 
  [c14]
  Adam Tsakalidis,Maria Liakata,Theodoros Damoulas,Brigitte Jellinek,Weisi Guo,Alexandra I. Cristea:
  Combining Heterogeneous User Generated Data to Sense Well-being.COLING2016:3007-3018
• 
  [c13]
  Henry Crosby,Paul Davis,Theodoros Damoulas,Stephen A. Jarvis:
  A spatio-temporal, Gaussian process regression, real-estate price predictor.SIGSPATIAL/GIS2016:68:1-68:4
• 
  [c12]
  Fernando Chirigati,Harish Doraiswamy,Theodoros Damoulas,Juliana Freire:
  Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets.SIGMOD Conference2016:1011-1025
• 
  [i2]
  Fernando Chirigati,Harish Doraiswamy,Theodoros Damoulas,Juliana Freire:
  Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets.CoRRabs/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 Cities2015
• 
  [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.AAAI2015:644-650
• 
  [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 Press2015, ISBN978-1-57735-715-5[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.ICPR2014:4429-4434
• 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.AAAI2013:1284-1290
• 
  [c7]
  Yexiang Xue,Bistra Dilkina,Theodoros Damoulas,Daniel Fink,Carla P. Gomes,Steve Kelling:
  Improving Your Chances: Boosting Citizen Science Discovery.HCOMP2013:198-206
• 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.IAAI2012:2229-2236
• 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.CP2011:508-522
• 2010
• 
  [j4]
  Ioannis Psorakis,Theodoros Damoulas,Mark A. Girolami:
  Multiclass relevance vector machines: sparsity and accuracy.IEEE Trans. Neural Networks21(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.ICMLA2010:424-429

• 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.PRIB2009:427-438
• 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.ICMLA2008:577-582
• 2005
• 
  [c1]
  Theodoros Damoulas,Ignasi Cos-Aguilera,Gillian M. Hayes,Tim Taylor:
  Valency for Adaptive Homeostatic Agents: Relating Evolution and Learning.ECAL2005:936-945

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