K. Seeliger
Geciteerd door
Geciteerd door
Convolutional neural network-based encoding and decoding of visual object recognition in space and time
K Seeliger, M Fritsche, U Güçlü, S Schoenmakers, JM Schoffelen, ...
NeuroImage 180, 253-266, 2018
Generative adversarial networks for reconstructing natural images from brain activity
K Seeliger, U Güçlü, L Ambrogioni, Y Güçlütürk, MAJ van Gerven
NeuroImage 181, 775-785, 2018
Reconstructing perceived faces from brain activations with deep adversarial neural decoding
Y Güçlütürk, U Güçlü, K Seeliger, SE Bosch, R van Lier, MAJ van Gerven
Advances in Neural Information Processing Systems, 4246-4257, 2017
Simulation data mining for supporting bridge design
S Burrows, B Stein, J Frochte, D Wiesner, K Müller
Proceedings of the Ninth Australasian Data Mining Conference-Volume 121, 163-170, 2011
End-to-end neural system identification with neural information flow
K Seeliger, L Ambrogioni, Y Güçlütürk, LM van den Bulk, U Güçlü, ...
PLOS Computational Biology 17 (2), e1008558, 2021
You Only Look on Lymphocytes Once
M van Rijthoven, Z Swiderska-Chadaj, K Seeliger, J van der Laak, ...
Current Advances in Neural Decoding
MAJ van Gerven, K Seeliger, U Güçlü, Y Güçlütürk
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 379-394, 2019
A large single-participant fMRI dataset for probing brain responses to naturalistic stimuli in space and time
K Seeliger, RP Sommers, U Güçlü, SE Bosch, MAJ van Gerven
bioRxiv, 687681, 2019
Brain2Pix: Fully convolutional naturalistic video reconstruction from brain activity
L Le, L Ambrogioni, K Seeliger, Y Güçlütürk, M van Gerven, U Güçlü
Modeling cognitive processes with neural reinforcement learning
SE Bosch, K Seeliger, MAJ van Gerven
bioRxiv, 084111, 2016
From photos to sketches - how humans and deep neural networks process objects across different levels of visual abstraction
J Singer, K Seeliger, TC Kietzmann, MN Hebart
PsyArXiv, 2021
Neural information flow: Learning neural information processing systems from brain activity
K Seeliger, L Ambrogioni, U Güçlü, MAJ van Gerven
2019 Conference on Cognitive Computational Neuroscience, 2019
Synthesizing preferred stimuli for individual voxels in the human visual system
K Seeliger, J Roth, T Schmid, M Hebart
Journal of Vision 21 (9), 2311-2311, 2021
Convolutional neural networks in vision neuroscience
K Seeliger
[Sl: sn], 2020
The representation of object drawings and sketches in deep convolutional neural networks
J Singer, K Seeliger, MN Hebart
NeurIPS workshop on Shared Visual Representations in Human & Machine …, 2020
A Large Single-Participant Functional Magnetic Resonance Imaging Data Set for Probing Brain Responses to Naturalistic Stimuli in Space and Time
K Seeliger, RP Sommers, U Guclu, SE Bosch, MAJ van Gerven
PERCEPTION 48, 5-6, 2019
Generalization of an upper bound on the number of nodes needed to achieve linear separability
M Troost, K Seeliger, MAJ van Gerven
arXiv preprint arXiv:1802.03488, 2018
Deep Learning with Symbols Hackathon
DL Silver, JC Davidson, D Hupkes, I Noble, K Seeliger
Human-Like Neural-Symbolic Computing 2 (10), 80, 2017
Detecting spatial auditory attention in cocktail-party situations
M Tangermann, K Mueller, A Nolte, J Schumacher, P Zhutovsky, ...
Clinical Neurophysiology, S147, 2014
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Artikelen 1–19