142 citations · 258 across the 16 of their papers we have counts for
4 papers · 1 filter
CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data
Mostafa Mehdipour Ghazi, Lauge Sørensen, Sébastien Ourselin +1
Learning temporal patterns from multivariate longitudinal data is challenging especially in cases when data is sporadic, as often seen in, e.g., healthcare applications where the d…
Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts
Svetlana Kutuzova, Oswin Krause, Douglas McCloskey +2
Multimodal generative models should be able to learn a meaningful latent representation that enables a coherent joint generation of all modalities (e.g., images and text). Many app…
On the Initialization of Long Short-Term Memory Networks
Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai +4
Weight initialization is important for faster convergence and stability of deep neural networks training. In this paper, a robust initialization method is developed to address the…
Knowledge distillation for semi-supervised domain adaptation
Mauricio Orbes-Arteaga, Jorge Cardoso, Lauge Sørensen +5
In the absence of sufficient data variation (e.g., scanner and protocol variability) in annotated data, deep neural networks (DNNs) tend to overfit during training. As a result, th…