Máté Lengyel

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Jozsef FiserCentral European UniversityPatvirtintas el. paštas ceu.edu
Gergo OrbanHead, Computational Systems Neuroscience Lab, HUN-REN Wigner Research Centre, Budapest, HungaryPatvirtintas el. paštas wigner.hu
Pietro BerkesPatvirtintas el. paštas brandeis.edu
Daniel WolpertProfessor of Neuroscience, Columbia UniversityPatvirtintas el. paštas columbia.edu
Peter ErdiKalamazoo CollegePatvirtintas el. paštas kzoo.edu
Guillaume HennequinProfessor of Computational Neuroscience, University of Cambridge, UKPatvirtintas el. paštas cam.ac.uk
Ferenc HuszárUniversity of CambridgePatvirtintas el. paštas cam.ac.uk
Laurence AitchisonUniversity of BristolPatvirtintas el. paštas bristol.ac.uk
Richard AslinYale UniversityPatvirtintas el. paštas yale.edu
Neil HoulsbyGooglePatvirtintas el. paštas google.com
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GooglePatvirtintas el. paštas eng.cam.ac.uk
Balazs B UjfalussyMTA Institute of Experimental MedicinePatvirtintas el. paštas koki.mta.hu
Boris GutkinEcole Normale SuperieurePatvirtintas el. paštas ens.fr
Cristina SavinNYUPatvirtintas el. paštas nyu.edu
Jean-Pascal PfisterProfessor of Theoretical Neuroscience, Department of Physiology, University of BernPatvirtintas el. paštas unibe.ch
Scott Cheng-Hsin YangRedpollPatvirtintas el. paštas redpoll.ai
Tiago BrancoUCL Sainsbury Wellcome CentrePatvirtintas el. paštas ucl.ac.uk
Jeehyun KwagSeoul National UniversityPatvirtintas el. paštas snu.ac.kr
Michiel Remme

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Máté Lengyel

Professor of Computational Neuroscience, University of Cambridge; Senior Research Fellow, CEU

Patvirtintas el. paštas eng.cam.ac.uk - Pagrindinis puslapis

computational neuroscience learning memory computational cognitive science


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Bayesian active learning for classification and preference learning N Houlsby, F Huszár, Z Ghahramani, M Lengyel arXiv preprint arXiv:1112.5745, 2011	970	2011
Statistically optimal perception and learning: from behavior to neural representations J Fiser, P Berkes, G Orbán, M Lengyel Trends in cognitive sciences 14 (3), 119-130, 2010	881	2010
Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment P Berkes, G Orbán, M Lengyel, J Fiser Science 331 (6013), 83-87, 2011	879	2011
Bayesian learning of visual chunks by human observers G Orbán, J Fiser, RN Aslin, M Lengyel Proceedings of the National Academy of Sciences 105 (7), 2745-2750, 2008	353	2008
With or without you: predictive coding and Bayesian inference in the brain L Aitchison, M Lengyel Current opinion in neurobiology 46, 219-227, 2017	337	2017
Hippocampal contributions to control: the third way M Lengyel, P Dayan Advances in neural information processing systems 20, 2007	324	2007
Neural variability and sampling-based probabilistic representations in the visual cortex G Orbán, P Berkes, J Fiser, M Lengyel Neuron 92 (2), 530-543, 2016	317	2016
Statistical treatment of looking-time data. G Csibra, M Hernik, O Mascaro, D Tatone, M Lengyel Developmental psychology 52 (4), 521, 2016	210	2016
Dynamically detuned oscillations account for the coupled rate and temporal code of place cell firing M Lengyel, Z Szatmáry, P Érdi Hippocampus 13 (6), 700-714, 2003	197	2003
Matching storage and recall: hippocampal spike timing–dependent plasticity and phase response curves M Lengyel, J Kwag, O Paulsen, P Dayan Nature neuroscience 8 (12), 1677-1683, 2005	181	2005
The dynamical regime of sensory cortex: stable dynamics around a single stimulus-tuned attractor account for patterns of noise variability G Hennequin, Y Ahmadian, DB Rubin, M Lengyel, KD Miller Neuron 98 (4), 846-860. e5, 2018	171	2018
Contextual inference underlies the learning of sensorimotor repertoires JB Heald, M Lengyel, DM Wolpert Nature 600 (7889), 489-493, 2021	167	2021
Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference R Echeveste, L Aitchison, G Hennequin, M Lengyel Nature Neuroscience 23, 1138–1149, 2020	142	2020
Theoretical perspectives on active sensing SCH Yang, DM Wolpert, M Lengyel Current opinion in behavioral sciences 11, 100-108, 2016	133	2016
Active sensing in the categorization of visual patterns SCH Yang, M Lengyel, DM Wolpert Elife 5, e12215, 2016	125	2016
Planning in the brain MG Mattar, M Lengyel Neuron 110 (6), 914-934, 2022	117	2022
Global and multiplexed dendritic computations under in vivo-like conditions BB Ujfalussy, JK Makara, M Lengyel, T Branco Neuron 100 (3), 579-592. e5, 2018	104	2018
Synapses with short-term plasticity are optimal estimators of presynaptic membrane potentials JP Pfister, P Dayan, M Lengyel Nature neuroscience 13 (10), 1271-1275, 2010	93	2010
The Hamiltonian brain: Efficient probabilistic inference with excitatory-inhibitory neural circuit dynamics L Aitchison, M Lengyel PLoS computational biology 12 (12), e1005186, 2016	89	2016
Fast sampling-based inference in balanced neuronal networks G Hennequin, L Aitchison, M Lengyel Advances in neural information processing systems 27, 2014	79	2014

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