4 citations · 7 across the 6 of their papers we have counts for
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cs.RO2019
A Perceived Environment Design using a Multi-Modal Variational Autoencoder for learning Active-Sensing
Timo Korthals, Malte Schilling, Jürgen Leitner
This contribution comprises the interplay between a multi-modal variational autoencoder and an environment to a perceived environment, on which an agent can act. Furthermore, we co…
cs.LG2019
MVAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood
Timo Korthals
This work gives an in-depth derivation of the trainable evidence lower bound obtained from the marginal joint log-Likelihood with the goal of training a Multi-Modal Variational Aut…