Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Kyriakos Efthymiadis"'
Autor:
Alexander Kensert, Emery Bosten, Gilles Collaerts, Kyriakos Efthymiadis, Peter Van Broeck, Gert Desmet, Deirdre Cabooter
Although commercially available software provides options for automatic peak detection, visual inspection and manual corrections are often needed. Peak detection algorithms commonly employed require carefully written rules and thresholds to increase
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d1302e57a2bd8d8745c0b717a602bb4
https://hdl.handle.net/20.500.14017/d6a293b8-3cdd-46b5-a220-9cc26b42e6c9
https://hdl.handle.net/20.500.14017/d6a293b8-3cdd-46b5-a220-9cc26b42e6c9
Autor:
Mahmoud Elbarbari, Florent Delgrange, Ivo Vervlimmeren, Kyriakos Efthymiadis, Bram Vanderborght, Ann Nowé
Reinforcement Learning (RL) enables artificial agents to learn through direct interaction with the environment. However, it usually does not scale up well to large problems due to its sampling inefficiency. Reward Shaping is a well-established approa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ce668e22ef303090b396121b1ffa8e3d
https://biblio.vub.ac.be/vubir/a-framework-for-flexibly-guiding-learning-agents(bf4975ae-0cc0-4ec3-a3f2-403a8a91072e).html
https://biblio.vub.ac.be/vubir/a-framework-for-flexibly-guiding-learning-agents(bf4975ae-0cc0-4ec3-a3f2-403a8a91072e).html
Autor:
Leander Schietgat, Bertrand Cuissart, Kurt De Grave, Kyriakos Efthymiadis, Ronan Bureau, Bruno Crémilleux, Jan Ramon, Alban Lepailleur
Publikováno v:
Molecular Informatics
Molecular Informatics, In press, ⟨10.1002/minf.202200232⟩
Molecular Informatics, In press, ⟨10.1002/minf.202200232⟩
International audience; Maximum common substructures (MCS) have received a lot of attention in the chemoinformatics community. They are typically used as a similarity measure between molecules, showing high predictive performance when used in classif
Publikováno v:
Diana Gomes
Vrije Universiteit Brussel
Vrije Universiteit Brussel
Graph neural networks (GNNs) are commonly applied to graph data, but their performance is often poorly understood. It is easy to find examples in which a GNN is unable to learn useful graph representations, but generally hard to explain why. In this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::d471160ee24959c8752dda78dc2c91fa
https://hdl.handle.net/20.500.14017/32ca501f-4fca-4f93-aa63-3faddcac7648
https://hdl.handle.net/20.500.14017/32ca501f-4fca-4f93-aa63-3faddcac7648
Autor:
Kyriakos Efthymiadis, Peter Van Broeck, Robbin Bouwmeester, Alexander Kensert, Gert Desmet, Deirdre Cabooter
Publikováno v:
Analytical chemistry. 93(47)
Machine learning is a popular technique to predict the retention times of molecules based on descriptors. Descriptors and associated labels (e.g., retention times) of a set of molecules can be used to train a machine learning algorithm. However, desc
Publikováno v:
Vrije Universiteit Brussel
Reinforcement Learning usually does not scale up well to large problems. It typically takes a Reinforcement Learning agent many trials until it can reach a satisfying policy. A main contributing factor to this problem is the fact that Reinforcement L
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::18b153b4968ab830f6985d3e3d10e57c
https://biblio.vub.ac.be/vubir/ltlfbased-reward-shaping-for-reinforcement-learning(e0f6c995-777d-4b30-a90e-60368c234c05).html
https://biblio.vub.ac.be/vubir/ltlfbased-reward-shaping-for-reinforcement-learning(e0f6c995-777d-4b30-a90e-60368c234c05).html
Autor:
Kyriakos Efthymiadis, Alexander Kensert, Peter Van Broeck, Deirdre Cabooter, Gert Desmet, Gilles Collaerts
Enhancement of chromatograms, such as the reduction of baseline noise and baseline drift, is often essential to accurately detect and quantify analytes in a mixture. Current methods have been well studied and adopted for decades and have assisted res
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00507979ac0f99abf6932b78813fbb28
https://lirias.kuleuven.be/handle/123456789/674135
https://lirias.kuleuven.be/handle/123456789/674135
An important challenge in chromatography is the development of adequate separation methods. Accurate retention models can significantly simplify and expedite the development of adequate separation methods for complex mixtures. The purpose of this stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ef9651e13cd3cbe10cd4b9bf337c177e
https://hdl.handle.net/20.500.14017/aa5235af-9d15-4c1b-8400-21a8077ceb9a
https://hdl.handle.net/20.500.14017/aa5235af-9d15-4c1b-8400-21a8077ceb9a
Autor:
Arnau Dillen, Denis Steckelmacher, Kyriakos Efthymiadis, Kevin Langlois, Albert De Beir, Uros Marusic, Bram Vanderborght, Ann Nowé, Romain Meeusen, Fakhreddine Ghaffari, Olivier Romain, Kevin De Pauw
Publikováno v:
Journal of Neural Engineering. 19:011003
Objective. Biosignal control is an interaction modality that allows users to interact with electronic devices by decoding the biological signals emanating from the movements or thoughts of the user. This manner of interaction with devices can enhance
Publikováno v:
Vrije Universiteit Brussel
Method development is an essential procedure to achieve the full potential of a chromatographic separation. However, since it is intrinsically a multi-parameter optimisation problem, this procedure can be quite complex and time-consuming. This is esp