David G. Nagy
David G. Nagy
PhD student, Computational Systems Neuroscience Lab, Wigner Research Centre for Physics
Verified email at - Homepage
Cited by
Cited by
Episodic memory as a prerequisite for online updates of model structure.
DG Nagy, G Orban
CogSci, 2016
Measuring and filtering reactive inhibition is essential for assessing serial decision making and learning.
B Török, K Janacsek, DG Nagy, G Orbán, D Nemeth
Journal of Experimental Psychology: General 146 (4), 529, 2017
Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signals
T Flesch, DG Nagy, A Saxe, C Summerfield
PLOS Computational Biology 19 (1), e1010808, 2023
Optimal forgetting: Semantic compression of episodic memories
DG Nagy, B Török, G Orbán
PLoS Computational Biology 16 (10), e1008367, 2020
Semantic compression of episodic memories
DG Nagy, B Török, G Orbán
arXiv preprint arXiv:1806.07990, 2018
Tracking the contribution of inductive bias to individualised internal models
B Török, DG Nagy, M Kiss, K Janacsek, D Németh, G Orbán
PLOS Computational Biology 18 (6), e1010182, 2022
Hierarchical semantic compression predicts texture selectivity in early vision
M Bányai, DG Nagy, G Orbán
Proceedings of the Conference on Cognitive Computational Neuroscience, 2019
Forgetting in delayed recognition as generative compression with decreasing capacity
C Frater, DG Nagy, G Orbán
Proceedings of the Annual Meeting of the Cognitive Science Society 44 (44), 2022
Memory Failures Provide Clues for more Efficient Compression
DG Nagy, C Fráter, G Orbán
Brain-inspired Computing, 25, 2021
Variational Autoencoder account of the early visual hierarchy
G Orban, M Banyai, D Nagy
Computational and Systems Neuroscience Meeting (COSYNE 2020), 165-166, 2020
Mechanisms of sharp wave-ripple generation and autonomous replay in a hippocampal network model
S Káli, E Vértes, DG Nagy, TF Freund, AI Gulyás
BMC Neuroscience 14, 1-2, 2013
A simple classical explanation for question order effects
DG Nagy
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