58 citations · 126 across the 8 of their papers we have counts for
3 papers · 1 filter
A Review of the Gumbel-max Trick and its Extensions for Discrete Stochasticity in Machine Learning
Iris A. M. Huijben, Wouter Kool, Max B. Paulus +1
The Gumbel-max trick is a method to draw a sample from a categorical distribution, given by its unnormalized (log-)probabilities. Over the past years, the machine learning communit…
Dynamic Probabilistic Pruning: A general framework for hardware-constrained pruning at different granularities
Lizeth Gonzalez-Carabarin, Iris A. M. Huijben, Bastiaan S. Veeling +2
Unstructured neural network pruning algorithms have achieved impressive compression rates. However, the resulting - typically irregular - sparse matrices hamper efficient hardware…
Overfitting for Fun and Profit: Instance-Adaptive Data Compression
Ties van Rozendaal, Iris A. M. Huijben, Taco S. Cohen
Neural data compression has been shown to outperform classical methods in terms of performance, with results still improving rapidly. At a high level, neural compression is ba…