200 citations · 221 across the 4 of their papers we have counts for
4 papers · 1 filter
Neural Bayesian Network Understudy
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 inabil…
A learning gap between neuroscience and reinforcement learning
Samuel T. Wauthier, Pietro Mazzaglia, Ozan Çatal +3
Historically, artificial intelligence has drawn much inspiration from neuroscience to fuel advances in the field. However, current progress in reinforcement learning is largely foc…
Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization
Cedric De Boom, Samuel Wauthier, Tim Verbelen +1
When designing variational autoencoders (VAEs) or other types of latent space models, the dimensionality of the latent space is typically defined upfront. In this process, it is po…
Learning Perception and Planning with Deep Active Inference
Ozan Çatal, Tim Verbelen, Johannes Nauta +2
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. However, current experiment…