16 citations · 24 across the 4 of their papers we have counts for
4 papers · 1 filter
Using State Predictions for Value Regularization in Curiosity Driven Deep Reinforcement Learning
Gino Brunner, Manuel Fritsche, Oliver Richter +1
Learning in sparse reward settings remains a challenge in Reinforcement Learning, which is often addressed by using intrinsic rewards. One promising strategy is inspired by human c…
MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style Transfer
Gino Brunner, Andres Konrad, Yuyi Wang +1
We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of handling polyphonic music with multiple instrument tracks, as well as modeling th…
Symbolic Music Genre Transfer with CycleGAN
Gino Brunner, Yuyi Wang, Roger Wattenhofer +1
Deep generative models such as Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) have recently been applied to style and domain transfer for images, and in…
Natural Language Multitasking: Analyzing and Improving Syntactic Saliency of Hidden Representations
Gino Brunner, Yuyi Wang, Roger Wattenhofer +1
We train multi-task autoencoders on linguistic tasks and analyze the learned hidden sentence representations. The representations change significantly when translation and part-of-…