David G. Nagy

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Gergo OrbanHead, Computational Systems Neuroscience Lab, HUN-REN Wigner Research Centre, Budapest, HungaryVerified email at wigner.hu
Balázs TörökPhD student, Computational Systems Neuroscience Lab, Wigner Research Centre for PhysicsVerified email at wigner.mta.hu
Karolina JanacsekAssociate Professor, University of Greenwich, London, United KingdomVerified email at greenwich.ac.uk
Dezső NÉMETHCRNL, INSERM, Lyon, FranceVerified email at inserm.fr
Timo FleschResearch ScientistVerified email at psy.ox.ac.uk
Christopher SummerfieldUniversity of OxfordVerified email at psy.ox.ac.uk
Andrew SaxeProfessor, Gatsby Unit & Sainsbury Wellcome Centre, UCLVerified email at ucl.ac.uk
Mihály BányaiMax Planck Institute for Biological CyberneticsVerified email at tuebingen.mpg.de
Charley M. WuHuman and Machine Cognition Lab, University of TübingenVerified email at uni-tuebingen.de
Attila I. GulyasProfessor of Neurobiology, Institute of Eperimental Medicine, Hungarian Acad. Sci.Verified email at koki.hu
Eszter VértesDeepMindVerified email at google.com
Szabolcs KáliSenior research scientist, Institute of Experimental Medicine, Budapest, HungaryVerified email at koki.hu

David G. Nagy

University of Tübingen, Max Planck Institute for Biological Cybernetics

Verified email at tuebingen.mpg.de - Homepage

computational cognitive science machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Episodic memory as a prerequisite for online updates of model structure. DG Nagy, G Orban CogSci, 2016	45	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	41	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	39	2023
Optimal forgetting: Semantic compression of episodic memories DG Nagy, B Török, G Orbán PLoS Computational Biology 16 (10), e1008367, 2020	18	2020
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	10	2022
Semantic compression of episodic memories DG Nagy, B Török, G Orbán arXiv preprint arXiv:1806.07990, 2018	5	2018
Hierarchical semantic compression predicts texture selectivity in early vision M Bányai, DG Nagy, G Orbán Proceedings of the Conference on Cognitive Computational Neuroscience, 2019	4	2019
Harmonizing program induction with rate-distortion theory H Zhou, DG Nagy, CM Wu arXiv preprint arXiv:2405.05294, 2024	3	2024
Identifying transfer learning in the reshaping of inductive biases A Székely, B Török, M Kiss, K Janacsek, D Németh, G Orbán Open Mind 8, 1107-1128, 2024	1	2024
Variational autoencoder account of the early visual hierarchy G Orban, M Banyai, D Nagy Computational and Systems Neuroscience Meeting (COSYNE 2020), 165-166, 2020	1	2020
Harmonizing Program Induction with Rate-Distortion Theory CM Wu, DG Nagy, H Zhou arXiv, 2024		2024
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		2022
Memory Failures Provide Clues for more Efficient Compression DG Nagy, C Fráter, G Orbán Brain-inspired Computing, 25, 2021		2021
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		2013
Rate distortion trade-off in human memory DG Nagy, B ázs Torok, G Orbán
A simple classical explanation for question order effects DG Nagy

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