1 code implementation • 2 Jul 2016 • Cedric De Boom, Steven Van Canneyt, Thomas Demeester, Bart Dhoedt
Traditional textual representations, such as tf-idf, have difficulty grasping the semantic meaning of such texts, which is important in applications such as event detection, opinion mining, news recommendation, etc.
2 code implementations • 2 Jan 2018 • Cedric De Boom, Thomas Demeester, Bart Dhoedt
Recurrent neural networks are nowadays successfully used in an abundance of applications, going from text, speech and image processing to recommender systems.
1 code implementation • 9 May 2016 • Cedric De Boom, Sam Leroux, Steven Bohez, Pieter Simoens, Thomas Demeester, Bart Dhoedt
We present four training and prediction schedules from the same character-level recurrent neural network.
1 code implementation • 22 Apr 2021 • Samuel T. Wauthier, Pietro Mazzaglia, Ozan Çatal, Cedric De Boom, Tim Verbelen, Bart Dhoedt
Historically, artificial intelligence has drawn much inspiration from neuroscience to fuel advances in the field.
1 code implementation • 15 Nov 2022 • Paloma Rabaey, Cedric De Boom, Thomas Demeester
Bayesian Networks may be appealing for clinical decision-making due to their inclusion of causal knowledge, but their practical adoption remains limited as a result of their inability to deal with unstructured data.
no code implementations • 9 Jun 2018 • Pieter Van Molle, Tim Verbelen, Elias De Coninck, Cedric De Boom, Pieter Simoens, Bart Dhoedt
Learning-based approaches for robotic grasping using visual sensors typically require collecting a large size dataset, either manually labeled or by many trial and errors of a robotic manipulator in the real or simulated world.
no code implementations • 27 May 2016 • Sam Leroux, Steven Bohez, Cedric De Boom, Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt
In this paper we propose a technique which avoids the evaluation of certain convolutional filters in a deep neural network.
no code implementations • 2 Dec 2015 • Cedric De Boom, Steven Van Canneyt, Steven Bohez, Thomas Demeester, Bart Dhoedt
We therefore investigated several text representations as a combination of word embeddings in the context of semantic pair matching.
no code implementations • 30 Jan 2020 • Ozan Çatal, Tim Verbelen, Johannes Nauta, Cedric De Boom, Bart Dhoedt
Active inference is a process theory of the brain that states that all living organisms infer actions in order to minimize their (expected) free energy.
no code implementations • 21 Feb 2020 • Cedric De Boom, Stephanie Van Laere, Tim Verbelen, Bart Dhoedt
Music that is generated by recurrent neural networks often lacks a sense of direction and coherence.
no code implementations • 6 Mar 2020 • Ozan Çatal, Samuel Wauthier, Tim Verbelen, Cedric De Boom, Bart Dhoedt
Active inference is a theory that underpins the way biological agent's perceive and act in the real world.
no code implementations • 24 Mar 2020 • Cedric De Boom, Samuel Wauthier, Tim Verbelen, Bart Dhoedt
In case the dimensionality is not predefined, this parameter is usually determined using time- and resource-consuming cross-validation.
no code implementations • 14 Jul 2022 • James Marien, Sam Leroux, Bart Dhoedt, Cedric De Boom
We find that our framework can generate suitable cover art for most genres, and that the visual features adapt themselves to audio feature changes.
no code implementations • 7 Jun 2023 • Cedric De Boom, Michael Reusens
However, the quality and integrity of data-science-driven statistics rely on the accuracy and reliability of the data sources and the machine learning techniques that support them.