Kyriakos Efthymiadis
Kyriakos Efthymiadis
Postdoctoral Researcher Vrije Universiteit Brussel
Verified email at
Cited by
Cited by
Metagenomic sequencing at the epicenter of the Nigeria 2018 Lassa fever outbreak
LE Kafetzopoulou, ST Pullan, P Lemey, MA Suchard, DU Ehichioya, ...
Science 363 (6422), 74-77, 2019
Assessment of metagenomic Nanopore and Illumina sequencing for recovering whole genome sequences of chikungunya and dengue viruses directly from clinical samples
LE Kafetzopoulou, K Efthymiadis, K Lewandowski, A Crook, D Carter, ...
Eurosurveillance 23 (50), 1800228, 2018
Distilling deep reinforcement learning policies in soft decision trees
Y Coppens, K Efthymiadis, T Lenaerts, A Nowé, T Miller, R Weber, ...
Proceedings of the IJCAI 2019 workshop on explainable artificial …, 2019
Using Plan-Based Reward Shaping To Learn Strategies in StarCraft: Broodwar
K Efthymiadis, D Kudenko
Computational Intelligence and Games (CIG), 2013 IEEE Conference on, 2013
Knowledge revision for reinforcement learning with abstract MDPs
K Efthymiadis, S Devlin, D Kudenko
Proceedings of the 2014 international conference on Autonomous agents and …, 2014
Deep Multi-Agent Reinforcement Learning in a Homogeneous Open Population
R Radulescu, M Legrand, K Efthymiadis, DM Roijers, A Nowé
SWAT: Seamless web authentication technology
F Rochet, K Efthymiadis, FÃ Koeune, O Pereira
The World Wide Web Conference, 1579-1589, 2019
Graph convolutional networks for improved prediction and interpretability of chromatographic retention data
A Kensert, R Bouwmeester, K Efthymiadis, P Van Broeck, G Desmet, ...
Analytical Chemistry 93 (47), 15633-15641, 2021
Overcoming incorrect knowledge in plan-based reward shaping
K Efthymiadis, S Devlin, D Kudenko
The Knowledge Engineering Review 31 (1), 31-43, 2016
Overcoming Incorrect Knowledge in Plan-Based Reward Shaping
K Efthymiadis, S Devlin, D Kudenko
In Proceedings of the AAMAS Workshop on Adaptive and Learning Agents (ALA), 2012
Deep convolutional autoencoder for the simultaneous removal of baseline noise and baseline drift in chromatograms
A Kensert, G Collaerts, K Efthymiadis, P Van Broeck, G Desmet, ...
Journal of Chromatography A 1646, 462093, 2021
Deep learning for biosignal control: insights from basic to real-time methods with recommendations
A Dillen, D Steckelmacher, K Efthymiadis, K Langlois, A De Beir, ...
Journal of Neural Engineering 19 (1), 011003, 2022
Deep Q-learning for the selection of optimal isocratic scouting runs in liquid chromatography
A Kensert, G Collaerts, K Efthymiadis, G Desmet, D Cabooter
Journal of Chromatography A 1638, 461900, 2021
Application of evolutionary algorithms to optimise one-and two-dimensional gradient chromatographic separations
B Huygens, K Efthymiadis, A Nowé, G Desmet
Journal of Chromatography A 1628, 461435, 2020
Overcoming erroneous domain knowledge in plan-based reward shaping
K Efthymiadis, S Devlin, D Kudenko
Proceedings of the 2013 international conference on autonomous agents and …, 2013
A Comparison of Plan-Based and Abstract MDP Reward Shaping
K Efthymiadis, D Kudenko
Ltlf-based reward shaping for reinforcement learning
M Elbarbari, K Efthymiadis, B Vanderborght, A Nowé
Adaptive and Learning Agents Workshop 2021, 2021
Convolutional neural network for automated peak detection in reversed-phase liquid chromatography
A Kensert, E Bosten, G Collaerts, K Efthymiadis, P Van Broeck, G Desmet, ...
Journal of Chromatography A 1672, 463005, 2022
Training a Speech-to-Text Model for Dutch on the Corpus Gesproken Nederlands.
W Röpke, R Radulescu, K Efthymiadis, A Nowé
York reinforcement learning library (yorll)
P Scopes, V Agarwal, S Devlin, K Efthymiadis, K Malialis, DT Kentse, ...
reinforcement Learning Group, Department of Computer Science, 2012
The system can't perform the operation now. Try again later.
Articles 1–20