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cs.LG2023★ 2 cited
How good are variational autoencoders at transfer learning?
Lisa Bonheme, Marek Grzes
Variational autoencoders (VAEs) are used for transfer learning across various research domains such as music generation or medical image analysis. However, there is no principled w…
cs.LG2022★ 1 cited
FONDUE: an algorithm to find the optimal dimensionality of the latent representations of variational autoencoders
Lisa Bonheme, Marek Grzes
When training a variational autoencoder (VAE) on a given dataset, determining the optimal number of latent variables is mostly done by grid search: a costly process in terms of com…
cs.LG2018
Reinforcement Learning using Augmented Neural Networks
Jack Shannon, Marek Grzes
Neural networks allow Q-learning reinforcement learning agents such as deep Q-networks (DQN) to approximate complex mappings from state spaces to value functions. However, this als…