Robustifying the Viterbi Algorithm. - Cedric De Boom; Jasper De Bock; Arthur Van Camp; Gert de Cooman (Probabilistic Graphical Models, 2014)

Learning Semantic Similarity for Very Short Texts. - Cedric De Boom; Steven Van Canneyt; Steven Bohez; Thomas Demeester; Bart Dhoedt (ICDM Workshops, 2015)

Optimizing the Popularity of Twitter Messages through User Categories. - Rupert Lemahieu; Steven Van Canneyt; Cedric De Boom; Bart Dhoedt (ICDM Workshops, 2015)

Semantics-driven Event Clustering in Twitter Feeds. - Cedric De Boom; Steven Van Canneyt; Bart Dhoedt (#MSM, 2015)

Structured Output Prediction for Semantic Perception in Autonomous Vehicles. - Rein Houthooft; Cedric De Boom; Stijn Verstichel; Femke Ongenae; Filip De Turck (AAAI, 2016)

Efficiency Evaluation of Character-level RNN Training Schedules. - Cedric De Boom; Sam Leroux; Steven Bohez; Pieter Simoens; Thomas Demeester; Bart Dhoedt (CoRR, 2016)

Lazy Evaluation of Convolutional Filters. - Sam Leroux; Steven Bohez; Cedric De Boom; Elias De Coninck; Tim Verbelen; Bert Vankeirsbilck; Pieter Simoens; Bart Dhoedt (CoRR, 2016)

Representation learning for very short texts using weighted word embedding aggregation. - Cedric De Boom; Steven Van Canneyt; Thomas Demeester; Bart Dhoedt (Pattern Recognit. Lett., 2016)

Low-latency delivery of news-based video content. - Jeroen van der Hooft; Dries Pauwels; Cedric De Boom; Stefano Petrangeli; Tim Wauters; Filip De Turck (MMSys, 2018)

An HTTP/2 push-based framework for low-latency adaptive streaming through user profiling. - Jeroen van der Hooft; Cedric De Boom; Stefano Petrangeli; Tim Wauters; Filip De Turck (NOMS, 2018)

Performance Characterization of Low-Latency Adaptive Streaming From Video Portals. - Jeroen van der Hooft; Cedric De Boom; Stefano Petrangeli; Tim Wauters; Filip De Turck (IEEE Access, 2018)

Learning to Grasp from a Single Demonstration. - Pieter Van Molle; Tim Verbelen; Elias De Coninck; Cedric De Boom; Pieter Simoens; Bart Dhoedt (CoRR, 2018)

Large-scale user modeling with recurrent neural networks for music discovery on multiple time scales. - Cedric De Boom; Rohan Agrawal; Samantha Hansen; Esh Kumar; Romain Yon; Ching-Wei Chen; Thomas Demeester; Bart Dhoedt (Multim. Tools Appl., 2018)

Quantifying Uncertainty of Deep Neural Networks in Skin Lesion Classification. - Pieter Van Molle; Tim Verbelen; Cedric De Boom; Bert Vankeirsbilck; Jonas De Vylder; Bart Diricx; Tom Kimpe; Pieter Simoens; Bart Dhoedt (UNSURE/CLIP@MICCAI, 2019)

Rhythm, Chord and Melody Generation for Lead Sheets Using Recurrent Neural Networks. - Cedric De Boom; Stephanie Van Laere; Tim Verbelen; Bart Dhoedt (PKDD/ECML Workshops (2), 2019)

Character-level recurrent neural networks in practice: comparing training and sampling schemes. - Cedric De Boom; Thomas Demeester; Bart Dhoedt (Neural Comput. Appl., 2019)

Learning Perception and Planning With Deep Active Inference. - Ozan Çatal; Tim Verbelen; Johannes Nauta; Cedric De Boom; Bart Dhoedt (ICASSP, 2020)

Anomaly Detection for Autonomous Guided Vehicles using Bayesian Surprise. - Ozan Çatal; Sam Leroux; Cedric De Boom; Tim Verbelen; Bart Dhoedt (IROS, 2020)

You Only Look as Much as You Have To - Using the Free Energy Principle for Active Vision. - Toon Van de Maele; Tim Verbelen; Ozan Çatal; Cedric De Boom; Bart Dhoedt (IWAI, 2020)

Sleep: Model Reduction in Deep Active Inference. - Samuel T. Wauthier; Ozan Çatal; Cedric De Boom; Tim Verbelen; Bart Dhoedt (IWAI, 2020)

Deep Active Inference for Autonomous Robot Navigation. - Ozan Çatal; Samuel Wauthier; Tim Verbelen; Cedric De Boom; Bart Dhoedt (CoRR, 2020)

Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization. - Cedric De Boom; Samuel Wauthier; Tim Verbelen; Bart Dhoedt (CoRR, 2020)

Learning Generative State Space Models for Active Inference. - Ozan Çatal; Samuel Wauthier; Cedric De Boom; Tim Verbelen; Bart Dhoedt (Frontiers Comput. Neurosci., 2020)

Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization. - Cedric De Boom; Samuel Wauthier; Tim Verbelen; Bart Dhoedt (IJCNN, 2021)

A learning gap between neuroscience and reinforcement learning. - Samuel T. Wauthier; Pietro Mazzaglia; Ozan Çatal; Cedric De Boom; Tim Verbelen; Bart Dhoedt (CoRR, 2021)

Active Vision for Robot Manipulators Using the Free Energy Principle. - Toon Van de Maele; Tim Verbelen; Ozan Çatal; Cedric De Boom; Bart Dhoedt (Frontiers Neurorobotics, 2021)

Data-Efficient Sensor Upgrade Path Using Knowledge Distillation. - Pieter Van Molle; Cedric De Boom; Tim Verbelen; Bert Vankeirsbilck; Jonas De Vylder; Bart Diricx; Pieter Simoens; Bart Dhoedt (Sensors, 2021)

Audio-guided Album Cover Art Generation with Genetic Algorithms. - James Marien; Sam Leroux; Bart Dhoedt; Cedric De Boom (CoRR, 2022)

Neural Bayesian Network Understudy. - Paloma Rabaey; Cedric De Boom; Thomas Demeester (CoRR, 2022)

Model Reduction Through Progressive Latent Space Pruning in Deep Active Inference. - Samuel T. Wauthier; Cedric De Boom; Ozan Çatal; Tim Verbelen; Bart Dhoedt (Frontiers Neurorobotics, 2022)

Changing Data Sources in the Age of Machine Learning for Official Statistics. - Cedric De Boom; Michael Reusens (CoRR, 2023)