Browsing by author "De Boom, Cedric"
Now showing items 1-20 of 23
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A learning gap between neuroscience and reinforcement learning
Wauthier, Samuel; Mazzaglia, Pietro; Catal, Ozan; De Boom, Cedric; Verbelen, Tim; Dhoedt, Bart (2021) -
Active Vision for Robot Manipulators Using the Free Energy Principle
Van de Maele, Toon; Verbelen, Tim; Catal, Ozan; De Boom, Cedric; Dhoedt, Bart (2021) -
An HTTP/2 push-based framework for low-latency adaptive streaming through user profiling
van der Hooft, Jeroen; De Boom, Cedric; Petrangeli, Stefano; Wauters, Tim; De Turck, Filip (2018-04) -
Character-level recurrent neural networks in practice: comparing training and sampling schemes
De Boom, Cedric; Demeester, Thomas; Dhoedt, Bart (2019) -
Deep active inference for autonomous robot navigation
Catal, Ozan; Wauthier, Samuel; Verbelen, Tim; De Boom, Cedric; Dhoedt, Bart (2020) -
Deep active inference for state estimation by learning from demonstration
De Boom, Cedric; Verbelen, Tim; Dhoedt, Bart (2018) -
Dermatologist versus artificial intelligence confidence in dermoscopy diagnosis: Complementary information that may affect decision-making
Van Molle, Pieter; Mylle, Sofie; Verbelen, Tim; De Boom, Cedric; Vankeirsbilck, Bert; Verhaeghe, Evelien; Dhoedt, Bart; Brochez, Lieve (2023) -
Dynamic Narrowing of VAE Bottlenecks Using GECO and L-0 Regularization
De Boom, Cedric; Wauthier, Samuel; Verbelen, Tim; Dhoedt, Bart (2021) -
Het leren van representaties voor symbolische sequenties
De Boom, Cedric (2018-05) -
Large-scale user modeling with recurrent neural networks for music discovery on multiple time scales
De Boom, Cedric; Agrawal, R.; Hansen, S.; Kumar, E.; Yon, R.; Chen, C.-W.; Demeester, Thomas; Dhoedt, Bart (2018) -
Learning generative state space models for active inference
Catal, Ozan; Wauthier, Samuel; De Boom, Cedric; Verbelen, Tim; Dhoedt, Bart (2020-11) -
LEARNING PERCEPTION AND PLANNING WITH DEEP ACTIVE INFERENCE
Catal, Ozan; Verbelen, Tim; Nauta, Johannes; De Boom, Cedric; Dhoedt, Bart (2020) -
Learning to Grasp from a single demonstration
Van Molle, Pieter; Verbelen, Tim; De Coninck, Elias; De Boom, Cedric; Simoens, Pieter; Dhoedt, Bart (2018-06) -
Low-latency delivery of news-based video content
van der Hooft, Jeroen; Pauwels, Dries; De Boom, Cedric; Petrangeli, Stefano; Wauters, Tim; De Turck, Filip (2018-06) -
Model Reduction Through Progressive Latent Space Pruning in Deep Active Inference
Wauthier, Samuel; De Boom, Cedric; Catal, Ozan; Verbelen, Tim; Dhoedt, Bart (2022) -
Neural Bayesian network understudy
Rabaey, Paloma; De Boom, Cedric; Demeester, Thomas (2022) -
Performance characterization of low-latency adaptive streaming from video portals
van der Hooft, Jeroen; De Boom, Cedric; Petrangeli, Stefano; Wauters, Tim; De Turck, Filip (2018) -
Quantifying uncertainty of deep neural networks in skin lesion classification
Van Molle, Pieter; Verbelen, Tim; De Boom, Cedric; Vankeirsbilck, Bert; De Vylder, Jona; Diricx, B.; Kimpe, T.; Simoens, Pieter; Dhoedt, Bart (2019) -
Rhythm, Chord and Melody Generation for Lead Sheets Using Recurrent Neural Networks
De Boom, Cedric; Van Laere, Stephanie; Verbelen, Tim; Dhoedt, Bart (2020) -
Sigmoidal NMFD: Convolutional NMF with Saturating Activations for Drum Mixture Decomposition
Vande Veire, Len; De Boom, Cedric; De Bie, Tijl (2021)