Ira Ktena

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Research Scientist @ Twitter || Data Science Consultant, Data Science Consultant at Imperial Consultants (ICON), Visiting Scientist at Harvard Medical School from 2017-2018, Scientific Project Officer at IMAGE ANALYSIS, GROUP from 2015- 2017, Scientific Programmer / Research Assistant at Imperial College London from 2013-2015, Software Developer / Research Assistant at Forecasting & Strategy Unit from 2008-2012

Featured Co-authors

Daniel Rueckert
121 publications
Pushmeet Kohli
90 publications
Oriol Vinyals
87 publications
Ben Glocker
74 publications
Bernhard Kainz
46 publications
Moritz Hardt
32 publications
Yujia Li
30 publications
Lucas Theis
25 publications
Michael Bronstein
24 publications
Enzo Ferrante
23 publications
Sven Gowal
22 publications

∙ 10/21/2021

A Fine-Grained Analysis on Distribution Shift

Robustness to distribution shifts is critical for deploying machine lear...

Olivia Wiles, et al. ∙

∙ 10/21/2021

Algorithmic Amplification of Politics on Twitter

Content on Twitter's home timeline is selected and ordered by personaliz...

Ferenc Huszár, et al. ∙

∙ 07/21/2021

Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs

Large Neighborhood Search (LNS) is a combinatorial optimization heuristi...

Nicolas Sonnerat, et al. ∙

∙ 12/23/2020

Solving Mixed Integer Programs Using Neural Networks

Mixed Integer Programming (MIP) solvers rely on an array of sophisticate...

Vinod Nair, et al. ∙

∙ 08/03/2020

Deep Bayesian Bandits: Exploring in Online Personalized Recommendations

Recommender systems trained in a continuous learning fashion are plagued...

Dalin Guo, et al. ∙

∙ 07/28/2020

Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems

Deep Neural Networks (DNNs) with sparse input features have been widely ...

Caojin Zhang, et al. ∙

∙ 04/28/2020

Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline

Recommender systems constitute the core engine of most social network pl...

Luca Belli, et al. ∙

∙ 07/15/2019

Addressing Delayed Feedback for Continuous Training with Neural Networks in CTR prediction

One of the challenges in display advertising is that the distribution of...

Ira Ktena, et al. ∙

∙ 06/05/2018

Graph Saliency Maps through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity

Graph convolutional networks (GCNs) allow to apply traditional convoluti...

Salim Arslan, et al. ∙

∙ 06/05/2018

Disease Prediction using Graph Convolutional Networks: Application to Autism Spectrum Disorder and Alzheimer's Disease

Graphs are widely used as a natural framework that captures interactions...

Sarah Parisot, et al. ∙

∙ 11/18/2017

DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images

We present DLTK, a toolkit providing baseline implementations for effici...

Nick Pawlowski, et al. ∙

∙ 03/29/2017

Exploring Heritability of Functional Brain Networks with Inexact Graph Matching

Data-driven brain parcellations aim to provide a more accurate represent...

Ira Ktena, et al. ∙

∙ 03/08/2017

Spectral Graph Convolutions for Population-based Disease Prediction

Exploiting the wealth of imaging and non-imaging information for disease...

Sarah Parisot, et al. ∙

∙ 03/07/2017

Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks

Evaluating similarity between graphs is of major importance in several c...

Ira Ktena, et al. ∙

∙ 11/15/2016

Comparison of Brain Networks with Unknown Correspondences

Graph theory has drawn a lot of attention in the field of Neuroscience d...

Ira Ktena, et al. ∙