24 citations · 76 across the 25 of their papers we have counts for
3 papers · 1 filter
Deep adversarial neural decoding
Yağmur Güçlütürk, Umut Güçlü, Katja Seeliger +3
Here, we present a novel approach to solve the problem of reconstructing perceived stimuli from brain responses by combining probabilistic inference with deep learning. Our approac…
The Kernel Mixture Network: A Nonparametric Method for Conditional Density Estimation of Continuous Random Variables
Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven +1
This paper introduces the kernel mixture network, a new method for nonparametric estimation of conditional probability densities using neural networks. We model arbitrarily complex…
End-to-end semantic face segmentation with conditional random fields as convolutional, recurrent and adversarial networks
Umut Güçlü, Yağmur Güçlütürk, Meysam Madadi +5
Recent years have seen a sharp increase in the number of related yet distinct advances in semantic segmentation. Here, we tackle this problem by leveraging the respective strengths…