53 citations · 113 across the 16 of their papers we have counts for
4 papers · 1 filter
Evolutionary Variational Optimization of Generative Models
Jakob Drefs, Enrico Guiraud, Jörg Lücke
We combine two popular optimization approaches to derive learning algorithms for generative models: variational optimization and evolutionary algorithms. The combination is realize…
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents
Enrico Guiraud, Jakob Drefs, Jörg Lücke
Discrete latent variables are considered important for real world data, which has motivated research on Variational Autoencoders (VAEs) with discrete latents. However, standard VAE…
The ELBO of Variational Autoencoders Converges to a Sum of Three Entropies
Simon Damm, Dennis Forster, Dmytro Velychko +3
The central objective function of a variational autoencoder (VAE) is its variational lower bound (the ELBO). Here we show that for standard (i.e., Gaussian) VAEs the ELBO converges…
Phase transition for parameter learning of Hidden Markov Models
Nikita Rau, Jörg Lücke, Alexander K. Hartmann
We study a phase transition in parameter learning of Hidden Markov Models (HMMs). We do this by generating sequences of observed symbols from given discrete HMMs with uniformly dis…