6 citations · 20 across the 15 of their papers we have counts for
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cs.LG2022
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…
cs.LG2019
System Identification with Time-Aware Neural Sequence Models
Thomas Demeester
Established recurrent neural networks are well-suited to solve a wide variety of prediction tasks involving discrete sequences. However, they do not perform as well in the task of…
cs.LG2018★ 5 cited
Character-level Recurrent Neural Networks in Practice: Comparing Training and Sampling Schemes
Cedric De Boom, Thomas Demeester, Bart Dhoedt
Recurrent neural networks are nowadays successfully used in an abundance of applications, going from text, speech and image processing to recommender systems. Backpropagation throu…