Theodoros Damoulas

发表

Pattern Recognition

Theodoros Damoulas, Mark A. Girolami, M. Girolami, 1998, Encyclopedia of Information Systems.

Phylogenetic Gaussian Processes for Bat Echolocation

Mark Girolami, Theodoros Damoulas, Kate E. Jones, 2018 .

Combining Heterogeneous User Generated Data to Sense Well-being

Maria Liakata, Adam Tsakalidis, Weisi Guo, 2016, COLING.

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

Theodoros Damoulas, Jevgenij Gamper, David J. Armstrong, 2020, Monthly Notices of the Royal Astronomical Society.

Case study of error recovery and error propagation on ranger

Arshad Jhumka, Edward Chuah, Tommy Minyard, 2017 .

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

Cláudio T. Silva, Juliana Freire, Theodoros Damoulas, 2014, IEEE Transactions on Visualization and Computer Graphics.

Combining Information with a Bayesian Multi-class Multi-kernel Pattern Recognition Machine

Mark Girolami, Theodoros Damoulas, M. Girolami, 2010 .

Improving Your Chances: Boosting Citizen Science Discovery

Steve Kelling, Theodoros Damoulas, Bistra N. Dilkina, 2013, HCOMP.

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

Theodoros Damoulas, Jeremias Knoblauch, T. Damoulas, 2018, ICML.

Multi-task Causal Learning with Gaussian Processes pdf

Theodoros Damoulas, Javier Gonz'alez, Virginia Aglietti, 2020, NeurIPS.

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

Theodoros Damoulas, Alex Chohlas-Wood, Warren Reed, 2015, AAAI Workshop: AI for Cities.

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

Jun Yu, Steve Kelling, Jeff Gerbracht, 2012, IAAI.

Generalized Bayesian Filtering via Sequential Monte Carlo pdf

Ömer Deniz Akyildiz, Theodoros Damoulas, Ayman Boustati, 2020, ArXiv.

Non-separable Non-stationary random fields

Theodoros Damoulas, Mark F. J. Steel, Kangrui Wang, 2020, ICML.

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

Juliana Freire, Fernando Seabra Chirigati, Theodoros Damoulas, 2016, SIGMOD Conference.

Multi-resolution Multi-task Gaussian Processes

Theodoros Damoulas, Kangrui Wang, Mark Girolami, 2019, NeurIPS.

Arctic greening under future climate change predicted using machine learning

Richard G. Pearson, Steven J. Phillips, Theodoros Damoulas, 2011 .

Pattern recognition with a Bayesian kernel combination machine

Theodoros Damoulas, Mark A. Girolami, M. Girolami, 2009, Pattern Recognit. Lett..

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

Theodoros Damoulas, Andrew Farnsworth, Carla P. Gomes, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

Valency for Adaptive Homeostatic Agents: Relating Evolution and Learning

Theodoros Damoulas, Gillian M. Hayes, Tim Taylor, 2005, ECAL.

Log Gaussian Cox Process Networks pdf

Edwin V. Bonilla, Theodoros Damoulas, Virginia Aglietti, 2018, ArXiv.

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

Theodoros Damoulas, Jaimin Dave, Daniel Fink, 2013, AAAI.

Estimating Species Distributions—Across Space, Through Time, and with Features of the Environment

Steve Kelling, Cláudio T. Silva, Theodoros Damoulas, 2013, DS 2013.

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

Colin Campbell, Theodoros Damoulas, Mark A. Girolami, 2008, 2008 Seventh International Conference on Machine Learning and Applications.

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

Theodoros Damoulas, Mark A. Girolami, M. Girolami, 2008, Bioinform..

Efficient Inference in Multi-task Cox Process Models

Edwin V. Bonilla, Theodoros Damoulas, Virginia Aglietti, 2018, AISTATS.

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

Neil Dhir, Theodoros Damoulas, James Walsh, 2020, ArXiv.

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

Jun Yu, Steve Kelling, Jeff Gerbracht, 2012, AI Mag..

Crowdsourcing Meets Ecology: Hemisphere-Wide Spatiotemporal Species Distribution Models

Steve Kelling, Theodoros Damoulas, Carla P. Gomes, 2014, AI Mag..

Towards data-driven energy consumption forecasting of multi-family residential buildings: Feature selection via the Lasso

Theodoros Damoulas, Rishee K. Jain, Constantine Kontokosta, 2014 .

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

Stephen A. Jarvis, Theodoros Damoulas, Henry Crosby, 2018, Int. J. Geogr. Inf. Sci..

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

Theodoros Damoulas, Jack Jewson, Jeremias Knoblauch, 2018, NeurIPS.

Road and travel time cross-validation for urban modelling

Stephen A. Jarvis, Theodoros Damoulas, Henry Crosby, 2019, Int. J. Geogr. Inf. Sci..

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

Arshad Jhumka, Edward Chuah, Tommy Minyard, 2017, 2017 IEEE 24th International Conference on High Performance Computing (HiPC).

Multiclass Relevance Vector Machines: Sparsity and Accuracy

Theodoros Damoulas, Mark A. Girolami, Ioannis Psorakis, 2010, IEEE Transactions on Neural Networks.

Structured Variational Inference in Continuous Cox Process Models

Edwin V. Bonilla, Theodoros Damoulas, Sally Cripps, 2019, NeurIPS.

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

Stefano Ermon, Theodoros Damoulas, Bistra N. Dilkina, 2015, AAAI.

Artificial Intelligence Applied to Assistive Technologies and Smart Environments, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 12, 2016

Eric Eaton, Toby Walsh, Francesca Rossi, 2016, AAAI Workshop: Artificial Intelligence Applied to Assistive Technologies and Smart Environments.

Protein interaction sentence detection using multiple semantic kernels

Theodoros Damoulas, Mark A. Girolami, Tamara Polajnar, 2011, J. Biomed. Semant..

Constraint Reasoning and Kernel Clustering for Pattern Decomposition with Scaling

Ronan Le Bras, Theodoros Damoulas, Ashish Sabharwal, 2011, CP.

On the Constrained Least-cost Tour Problem pdf

M. S. Ramanujan, Theodoros Damoulas, Patrick O'Hara, 2019, ArXiv.

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

Anish Arora, Theodoros Damoulas, Carla P. Gomes, 2014, 2014 22nd International Conference on Pattern Recognition.

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

Colin Campbell, Theodoros Damoulas, Mark A. Girolami, 2009, PRIB.

Generalized Variational Inference: Three arguments for deriving new Posteriors

Theodoros Damoulas, Jack Jewson, Jeremias Knoblauch, 2019 .

Transforming Gaussian Processes With Normalizing Flows pdf

Theodoros Damoulas, Juan Maronas, Jeremias Knoblauch, 2020, ArXiv.

Distribution Regression for Sequential Data

Edwin V. Bonilla, Theodoros Damoulas, Terry Lyons, 2020, AISTATS.

Variational Autoencoding of PDE Inverse Problems pdf

Theodoros Damoulas, Daniel J. Tait, T. Damoulas, 2020, ArXiv.

Generalised Bayesian Filtering via Sequential Monte Carlo

Ömer Deniz Akyildiz, Theodoros Damoulas, Adam M. Johansen, 2020, NeurIPS.

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

Stephen A. Jarvis, Paul Davis, Theodoros Damoulas, 2016, SIGSPATIAL/GIS.

Probabilistic multiple kernel learning

Theodoros Damoulas, 2009 .

Generalized Variational Inference pdf

Theodoros Damoulas, Jack Jewson, Jeremias Knoblauch, 2019, ArXiv.

Reports on the 2015 AAAI workshop series

Eric Eaton, Gary F. Marcus, Cornelia Caragea, 2015 .

Near Real-Time Social Distancing in London pdf

Neil Dhir, Theodoros Damoulas, Andrew Wang, 2020, ArXiv.

Probabilistic sequential matrix factorization pdf

Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel, 2019, AISTATS.

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

Theodoros Damoulas, Terry Lyons, Cristopher Salvi, 2021, NeurIPS.

Dynamic Causal Bayesian Optimization pdf

Neil Dhir, Theodoros Damoulas, Virginia Aglietti, 2021, NeurIPS.

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

Theodoros Damoulas, Virginia Aglietti, Shanaka Perera, 2021, ArXiv.

Spatio-Temporal Variational Gaussian Processes pdf

Arno Solin, Theodoros Damoulas, Oliver Hamelijnck, 2021, NeurIPS.

Uncertainty-aware deep learning methods for robust diabetic retinopathy classification

Kimmo Kaski, Theodoros Damoulas, Leo Karkkainen, 2022 .

Probabilistic sequential matrix factorization

Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel, 2021, AISTATS.

SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data pdf

Edwin V. Bonilla, Theodoros Damoulas, Terry Lyons, 2021, ICML.

Distribution Regression for Sequential Data

Edwin V. Bonilla, Theodoros Damoulas, Terry Lyons, 2020, AISTATS.

AL 2 : Learning for Active Learning

Theodoros Damoulas, Carla P. Gomes, Bistra Dilkina, 2011 .