Theodoros Damoulas

According to our database1, Theodoros Damoulas authored at least 58 papers between 2005 and 2021.

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Bibliography

2021
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes.
CoRR, 2021

A variational Bayesian spatial interaction model for estimating revenue and demand at business facilities.
CoRR, 2021

SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data.
Proceedings of the 38th International Conference on Machine Learning, 2021

Transforming Gaussian Processes With Normalizing Flows.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Distribution Regression for Sequential Data.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Probabilistic Sequential Matrix Factorization.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Road and travel time cross-validation for urban modelling.
Int. J. Geogr. Inf. Sci., 2020

Posterior inference for sparse hierarchical non-stationary models.
Comput. Stat. Data Anal., 2020

Near Real-Time Social Distancing in London.
CoRR, 2020

An Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System.
CoRR, 2020

Exoplanet Validation with Machine Learning: 50 new validated Kepler planets.
CoRR, 2020

Variational Autoencoding of PDE Inverse Problems.
CoRR, 2020

Distribution Regression for Continuous-Time Processes via the Expected Signature.
CoRR, 2020

Generalized Bayesian Filtering via Sequential Monte Carlo.
CoRR, 2020

Bi-directional online transfer learning: a framework.
Ann. des Télécommunications, 2020

Generalised Bayesian Filtering via Sequential Monte Carlo.
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.
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.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Embedding road networks and travel time into distance metrics for urban modelling.
Int. J. Geogr. Inf. Sci., 2019

Probabilistic sequential matrix factorization.
CoRR, 2019

Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization.
CoRR, 2019

On the Constrained Least-cost Tour Problem.
CoRR, 2019

Generalized Variational Inference.
CoRR, 2019

Multi-resolution Multi-task Gaussian Processes.
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.
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.
Proceedings of the 8th International Workshop on Big Data, 2019

Efficient Inference in Multi-task Cox Process Models.
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.
Geo spatial Inf. Sci., 2018

Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences.
CoRR, 2018

Log Gaussian Cox Process Networks.
CoRR, 2018

Can We Assess Mental Health Through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with \beta-Divergences.
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.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Enabling Dependability-Driven Resource Use and Message Log-Analysis for Cluster System Diagnosis.
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.
Proceedings of the 2016 International Conference on Management of Data, 2016

A spatio-temporal, Gaussian process regression, real-estate price predictor.
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.
Proceedings of the COLING 2016, 2016

2015
Reports from the 2015 AAAI Workshop Program.
AI Mag., 2015

Learning Large-Scale Dynamic Discrete Choice Models of Spatio-Temporal Preferences with Application to Migratory Pastoralism in East Africa.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Mining 911 Calls in New York City: Temporal Patterns, Detection, and Forecasting.
Proceedings of the Artificial Intelligence for Cities, 2015

2014
Using Topological Analysis to Support Event-Guided Exploration in Urban Data.
IEEE Trans. Vis. Comput. Graph., 2014

Crowdsourcing Meets Ecology: Hemisphere-Wide Spatiotemporal Species Distribution Models.
AI Mag., 2014

String Kernels for Complex Time-Series: Counting Targets from Sensed Movement.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014

2013
A Human/Computer Learning Network to Improve Biodiversity Conservation and Research.
AI Mag., 2013

Improving Your Chances: Boosting Citizen Science Discovery.
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.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012
eBird: A Human/Computer Learning Network for Biodiversity Conservation and Research.
Proceedings of the Twenty-Fourth Conference on Innovative Applications of Artificial Intelligence, 2012

2011
Protein interaction sentence detection using multiple semantic kernels.
J. Biomed. Semant., 2011

Constraint Reasoning and Kernel Clustering for Pattern Decomposition with Scaling.
Proceedings of the Principles and Practice of Constraint Programming - CP 2011, 2011

2010
Multiclass relevance vector machines: sparsity and accuracy.
IEEE Trans. Neural Networks, 2010

Bayesian Classification of Flight Calls with a Novel Dynamic Time Warping Kernel.
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

2009
Probabilistic multiple kernel learning.
PhD thesis, 2009

Pattern recognition with a Bayesian kernel combination machine.
Pattern Recognit. Lett., 2009

Combining feature spaces for classification.
Pattern Recognit., 2009

Class Prediction from Disparate Biological Data Sources Using an Iterative Multi-Kernel Algorithm.
Proceedings of the Pattern Recognition in Bioinformatics, 2009

2008
Probabilistic multi-class multi-kernel learning: on protein fold recognition and remote homology detection.
Bioinform., 2008

Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

2005
Valency for Adaptive Homeostatic Agents: Relating Evolution and Learning.
Proceedings of the Advances in Artificial Life, 8th European Conference, 2005


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