output
20092022
most citedDeep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Brain's Ventral Visual Pathway

1.1k citations

Showing 2016Show all

6 papers · 1 filter

cs.CV2016★ 60 cited

Convolutional Sketch Inversion

Yağmur Güçlütürk, Umut Güçlü, Rob van Lier +1

In this paper, we use deep neural networks for inverting face sketches to synthesize photorealistic face images. We first construct a semi-simulated dataset containing a very large…

q-bio.NC2016★ 105 cited

Modeling the dynamics of human brain activity with recurrent neural networks

Umut Güçlü, Marcel A. J. van Gerven

Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encodin…

q-bio.NC2016★ 3 cited

Brains on Beats

Umut Güçlü, Jordy Thielen, Michael Hanke +1

We developed task-optimized deep neural networks (DNNs) that achieved state-of-the-art performance in different evaluation scenarios for automatic music tagging. These DNNs were su…

q-bio.NC2016★ 17 cited

Dynamic Decomposition of Spatiotemporal Neural Signals

Luca Ambrogioni, Marcel A. J. van Gerven, Eric Maris

Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks…

cs.LG2016★ 27 cited

Particle Smoothing for Hidden Diffusion Processes: Adaptive Path Integral Smoother

H. -Ch. Ruiz, H. J. Kappen

Particle smoothing methods are used for inference of stochastic processes based on noisy observations. Typically, the estimation of the marginal posterior distribution given all ob…

q-bio.QM2016★ 332 cited

Connectopic mapping with resting-state fMRI

Koen V. Haak, Andre F. Marquand, Christian F. Beckmann

Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or '…