C. D. Boom

发表

Active Inference: First International Workshop, IWAI 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14, 2020, Proceedings

Raquel Oliveira Prates, C. Buckley, Pablo Lanillos, 2020, IWAI.

Audio-guided Album Cover Art Generation with Genetic Algorithms

Sam Leroux, B. Dhoedt, C. D. Boom, 2022, ArXiv.

Sleep: Model Reduction in Deep Active Inference

Tim Verbelen, Bart Dhoedt, Cedric De Boom, 2020, IWAI.

Learning Generative State Space Models for Active Inference

Tim Verbelen, Bart Dhoedt, Cedric De Boom, 2020, Frontiers in Computational Neuroscience.

A learning gap between neuroscience and reinforcement learning pdf

Tim Verbelen, Bart Dhoedt, Cedric De Boom, 2021, ArXiv.

You Only Look as Much as You Have To - Using the Free Energy Principle for Active Vision

Tim Verbelen, Bart Dhoedt, Cedric De Boom, 2020, IWAI.

Neural Bayesian Network Understudy

C. D. Boom, Thomas Demeester, Paloma Rabaey, 2022, ArXiv.

Deep Active Inference for Autonomous Robot Navigation pdf

Tim Verbelen, Bart Dhoedt, Cedric De Boom, 2020, ICLR 2020.

Learning Perception and Planning With Deep Active Inference

Tim Verbelen, Bart Dhoedt, Cedric De Boom, 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Optimizing the Popularity of Twitter Messages through User Categories

Bart Dhoedt, Cedric De Boom, Steven Van Canneyt, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

Representation learning for very short texts using weighted word embedding aggregation

Thomas Demeester, Bart Dhoedt, Cedric De Boom, 2016, Pattern Recognit. Lett..

Lazy Evaluation of Convolutional Filters pdf

Steven Bohez, Tim Verbelen, Pieter Simoens, 2016, ICML 2016.

Quantifying Uncertainty of Deep Neural Networks in Skin Lesion Classification

Tim Verbelen, Pieter Simoens, Bart Dhoedt, 2019, UNSURE/CLIP@MICCAI.

Active Vision for Robot Manipulators Using the Free Energy Principle

Tim Verbelen, Bart Dhoedt, Cedric De Boom, 2021, Frontiers in Neurorobotics.

Deep active inference for state estimation by learning from demonstration

Tim Verbelen, Bart Dhoedt, Cedric De Boom, 2018 .

Data-Efficient Sensor Upgrade Path Using Knowledge Distillation

Tim Verbelen, Pieter Simoens, Bart Dhoedt, 2021, Sensors.

Anomaly Detection for Autonomous Guided Vehicles using Bayesian Surprise

Sam Leroux, Tim Verbelen, B. Dhoedt, 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization

Samuel T. Wauthier, Tim Verbelen, B. Dhoedt, 2020, 2021 International Joint Conference on Neural Networks (IJCNN).

Learning Semantic Similarity for Very Short Texts

Thomas Demeester, Steven Bohez, Bart Dhoedt, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

An HTTP/2 push-based framework for low-latency adaptive streaming through user profiling

Filip De Turck, Tim Wauters, Stefano Petrangeli, 2018, NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium.

Changing Data Sources in the Age of Machine Learning for Official Statistics

C. D. Boom, Michael Reusens, 2023, ArXiv.

Learning to Grasp from a Single Demonstration pdf

Tim Verbelen, Pieter Simoens, Bart Dhoedt, 2018, ArXiv.

Semantics-driven Event Clustering in Twitter Feeds

Bart Dhoedt, Cedric De Boom, Steven Van Canneyt, 2015, #MSM.