83 citations · 259 across the 11 of their papers we have counts for
3 papers · 1 filter
Learning Functional Causal Models with Generative Neural Networks
Olivier Goudet, Diviyan Kalainathan, Philippe Caillou +3
We introduce a new approach to functional causal modeling from observational data, called Causal Generative Neural Networks (CGNN). CGNN leverages the power of neural networks to l…
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…
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…