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Cedric De Boom
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2020 – today
- 2023
- [i15]Cedric De Boom, Michael Reusens:
Changing Data Sources in the Age of Machine Learning for Official Statistics. CoRR abs/2306.04338 (2023) - 2022
- [j8]Samuel T. Wauthier
, Cedric De Boom, Ozan Çatal, Tim Verbelen, Bart Dhoedt:
Model Reduction Through Progressive Latent Space Pruning in Deep Active Inference. Frontiers Neurorobotics 16: 795846 (2022) - [i14]James Marien, Sam Leroux, Bart Dhoedt, Cedric De Boom:
Audio-guided Album Cover Art Generation with Genetic Algorithms. CoRR abs/2207.07162 (2022) - [i13]Paloma Rabaey, Cedric De Boom, Thomas Demeester:
Neural Bayesian Network Understudy. CoRR abs/2211.08243 (2022) - 2021
- [j7]Toon Van de Maele, Tim Verbelen, Ozan Çatal, Cedric De Boom, Bart Dhoedt:
Active Vision for Robot Manipulators Using the Free Energy Principle. Frontiers Neurorobotics 15: 642780 (2021) - [j6]Pieter Van Molle
Data-Efficient Sensor Upgrade Path Using Knowledge Distillation. Sensors 21(19): 6523 (2021) - [c14]Cedric De Boom, Samuel Wauthier
Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization. IJCNN 2021: 1-8 - [i12]Samuel T. Wauthier
A learning gap between neuroscience and reinforcement learning. CoRR abs/2104.10995 (2021) - 2020
- [j5]Ozan Çatal, Samuel Wauthier
Learning Generative State Space Models for Active Inference. Frontiers Comput. Neurosci. 14: 574372 (2020) - [c13]Ozan Çatal, Tim Verbelen
Learning Perception and Planning With Deep Active Inference. ICASSP 2020: 3952-3956 - [c12]Ozan Çatal, Sam Leroux, Cedric De Boom, Tim Verbelen, Bart Dhoedt:
Anomaly Detection for Autonomous Guided Vehicles using Bayesian Surprise. IROS 2020: 8148-8153 - [c11]Samuel T. Wauthier
Sleep: Model Reduction in Deep Active Inference. IWAI 2020: 72-83 - [c10]Toon Van de Maele, Tim Verbelen, Ozan Çatal, Cedric De Boom, Bart Dhoedt:
You Only Look as Much as You Have To - Using the Free Energy Principle for Active Vision. IWAI 2020: 92-100 - [e1]Tim Verbelen
Active Inference - First International Workshop, IWAI 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14, 2020, Proceedings. Communications in Computer and Information Science 1326, Springer 2020, ISBN 978-3-030-64918-0 [contents] - [i11]Ozan Çatal, Tim Verbelen, Johannes Nauta, Cedric De Boom, Bart Dhoedt:
Learning Perception and Planning with Deep Active Inference. CoRR abs/2001.11841 (2020) - [i10]Cedric De Boom, Stephanie Van Laere, Tim Verbelen, Bart Dhoedt:
Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks. CoRR abs/2002.10266 (2020) - [i9]Ozan Çatal, Samuel Wauthier, Tim Verbelen, Cedric De Boom, Bart Dhoedt:
Deep Active Inference for Autonomous Robot Navigation. CoRR abs/2003.03220 (2020) - [i8]Cedric De Boom, Samuel Wauthier, Tim Verbelen, Bart Dhoedt:
Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization. CoRR abs/2003.10901 (2020)
2010 – 2019
- 2019
- [j4]Cedric De Boom
Character-level recurrent neural networks in practice: comparing training and sampling schemes. Neural Comput. Appl. 31(8): 4001-4017 (2019) - [c9]Pieter Van Molle, Tim Verbelen
Quantifying Uncertainty of Deep Neural Networks in Skin Lesion Classification. UNSURE/CLIP@MICCAI 2019: 52-61 - [c8]Cedric De Boom, Stephanie Van Laere, Tim Verbelen
Rhythm, Chord and Melody Generation for Lead Sheets Using Recurrent Neural Networks. PKDD/ECML Workshops (2) 2019: 454-461 - 2018
- [j3]Jeroen van der Hooft
Performance Characterization of Low-Latency Adaptive Streaming From Video Portals. IEEE Access 6: 43039-43055 (2018) - [j2]Cedric De Boom, Rohan Agrawal, Samantha Hansen, Esh Kumar, Romain Yon, Ching-Wei Chen, Thomas Demeester
Large-scale user modeling with recurrent neural networks for music discovery on multiple time scales. Multim. Tools Appl. 77(12): 15385-15407 (2018) - [c7]Jeroen van der Hooft, Dries Pauwels, Cedric De Boom, Stefano Petrangeli, Tim Wauters, Filip De Turck
Low-latency delivery of news-based video content. MMSys 2018: 537-540 - [c6]Jeroen van der Hooft, Cedric De Boom, Stefano Petrangeli, Tim Wauters, Filip De Turck:
An HTTP/2 push-based framework for low-latency adaptive streaming through user profiling. NOMS 2018: 1-5 - [i7]Cedric De Boom, Thomas Demeester, Bart Dhoedt:
Character-level Recurrent Neural Networks in Practice: Comparing Training and Sampling Schemes. CoRR abs/1801.00632 (2018) - [i6]Pieter Van Molle, Tim Verbelen, Elias De Coninck, Cedric De Boom, Pieter Simoens, Bart Dhoedt:
Learning to Grasp from a Single Demonstration. CoRR abs/1806.03486 (2018) - 2017
- [i5]Cedric De Boom, Rohan Agrawal, Samantha Hansen, Esh Kumar, Romain Yon, Ching-Wei Chen, Thomas Demeester, Bart Dhoedt:
Large-Scale User Modeling with Recurrent Neural Networks for Music Discovery on Multiple Time Scales. CoRR abs/1708.06520 (2017) - 2016
- [j1]Cedric De Boom, Steven Van Canneyt, Thomas Demeester
Representation learning for very short texts using weighted word embedding aggregation. Pattern Recognit. Lett. 80: 150-156 (2016) - [c5]Rein Houthooft, Cedric De Boom, Stijn Verstichel, Femke Ongenae, Filip De Turck:
Structured Output Prediction for Semantic Perception in Autonomous Vehicles. AAAI 2016: 3509-3515 - [i4]Cedric De Boom, Sam Leroux, Steven Bohez, Pieter Simoens, Thomas Demeester, Bart Dhoedt:
Efficiency Evaluation of Character-level RNN Training Schedules. CoRR abs/1605.02486 (2016) - [i3]Sam Leroux, Steven Bohez, Cedric De Boom, Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Lazy Evaluation of Convolutional Filters. CoRR abs/1605.08543 (2016) - [i2]Cedric De Boom, Steven Van Canneyt, Thomas Demeester, Bart Dhoedt:
Representation learning for very short texts using weighted word embedding aggregation. CoRR abs/1607.00570 (2016) - 2015
- [c4]Cedric De Boom, Steven Van Canneyt, Steven Bohez, Thomas Demeester
Learning Semantic Similarity for Very Short Texts. ICDM Workshops 2015: 1229-1234 - [c3]Rupert Lemahieu, Steven Van Canneyt, Cedric De Boom, Bart Dhoedt:
Optimizing the Popularity of Twitter Messages through User Categories. ICDM Workshops 2015: 1396-1401 - [c2]Cedric De Boom, Steven Van Canneyt, Bart Dhoedt:
Semantics-driven Event Clustering in Twitter Feeds. #MSM 2015: 2-9 - [i1]Cedric De Boom, Steven Van Canneyt, Steven Bohez, Thomas Demeester, Bart Dhoedt:
Learning Semantic Similarity for Very Short Texts. CoRR abs/1512.00765 (2015) - 2014
- [c1]Cedric De Boom, Jasper De Bock, Arthur Van Camp
Robustifying the Viterbi Algorithm. Probabilistic Graphical Models 2014: 160-175
Coauthor Index
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