13 citations · 20 across the 4 of their papers we have counts for
4 papers · 1 filter
Mixing Consistent Deep Clustering
Daniel Lutscher, Ali el Hassouni, Maarten Stol +1
Finding well-defined clusters in data represents a fundamental challenge for many data-driven applications, and largely depends on good data representation. Drawing on literature r…
FlipOut: Uncovering Redundant Weights via Sign Flipping
Andrei Apostol, Maarten Stol, Patrick Forré
Modern neural networks, although achieving state-of-the-art results on many tasks, tend to have a large number of parameters, which increases training time and resource usage. This…
Super-resolution Variational Auto-Encoders
Ioannis Gatopoulos, Maarten Stol, Jakub M. Tomczak
The framework of variational autoencoders (VAEs) provides a principled method for jointly learning latent-variable models and corresponding inference models. However, the main draw…
Pruning via Iterative Ranking of Sensitivity Statistics
Stijn Verdenius, Maarten Stol, Patrick Forré
With the introduction of SNIP [arXiv:1810.02340v2], it has been demonstrated that modern neural networks can effectively be pruned before training. Yet, its sensitivity criterion h…