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ORCIDMáté Lengyel
Person information
- affiliation: Department of Engineering, University of Cambridge, UK
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2020 – today
- 2023
[c22]David Liu, Máté Lengyel:
Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability. NeurIPS 2023- 2022
- [c21]Wayne Soo, Máté Lengyel:
Training stochastic stabilized supralinear networks by dynamics-neutral growth. NeurIPS 2022 - 2021
- [c20]David Liu, Máté Lengyel:
A universal probabilistic spike count model reveals ongoing modulation of neural variability. NeurIPS 2021: 13392-13405
2010 – 2019
- 2019
- [c19]Oana Stanciu, Máté Lengyel, József Fiser:
To Teach Better, Learn First. CogSci 2019: 2864-2870 - [c18]Yul Kang, Daniel M. Wolpert, Máté Lengyel:
Confirmation Bias Trumps Performance Optimization in Overt Active Learning. CogSci 2019: 3490 - 2018
- [c17]Alberto Bernacchia, Máté Lengyel, Guillaume Hennequin:
Exact natural gradient in deep linear networks and its application to the nonlinear case. NeurIPS 2018: 5945-5954 - 2017
- [c16]Oana Stanciu, Máté Lengyel, Daniel M. Wolpert, József Fiser:
Perceptual decision making from correlated samples. CogSci 2017 - 2016
- [j10]Laurence Aitchison
, Máté Lengyel:
The Hamiltonian Brain: Efficient Probabilistic Inference with Excitatory-Inhibitory Neural Circuit Dynamics. PLoS Comput. Biol. 12(12) (2016) - [c15]Jirí Cevora, Máté Lengyel, Richard N. Henson:
Is human learning driven by Prediction Error? CogSci 2016 - [c14]Daniel C. McNamee, Daniel M. Wolpert, Máté Lengyel:
Efficient state-space modularization for planning: theory, behavioral and neural signatures. NIPS 2016: 4511-4519 - 2014
- [j9]Cristina Savin, Peter Dayan, Máté Lengyel:
Optimal Recall from Bounded Metaplastic Synapses: Predicting Functional Adaptations in Hippocampal Area CA3. PLoS Comput. Biol. 10(2) (2014) - [c13]Dylan Festa, Guillaume Hennequin, Máté Lengyel:
Analog Memories in a Balanced Rate-Based Network of E-I Neurons. NIPS 2014: 2231-2239 - [c12]Guillaume Hennequin, Laurence Aitchison, Máté Lengyel:
Fast Sampling-Based Inference in Balanced Neuronal Networks. NIPS 2014: 2240-2248 - [c11]Sina Tootoonian, Máté Lengyel:
A Dual Algorithm for Olfactory Computation in the Locust Brain. NIPS 2014: 2276-2284 - 2013
- [c10]Cristina Savin, Peter Dayan, Máté Lengyel:
Correlations strike back (again): the case of associative memory retrieval. NIPS 2013: 288-296 - 2011
- [c9]Balázs Ujfalussy, Máté Lengyel:
Active dendrites: adaptation to spike-based communication. NIPS 2011: 1188-1196 - [c8]Cristina Savin, Peter Dayan, Máté Lengyel:
Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories. NIPS 2011: 1305-1313 - [i1]Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Máté Lengyel:
Bayesian Active Learning for Classification and Preference Learning. CoRR abs/1112.5745 (2011)
2000 – 2009
- 2009
- [j8]Michiel W. H. Remme, Máté Lengyel, Boris S. Gutkin:
The Role of Ongoing Dendritic Oscillations in Single-Neuron Dynamics. PLoS Comput. Biol. 5(9) (2009) - [c7]Jean-Pascal Pfister, Peter Dayan, Máté Lengyel:
Know Thy Neighbour: A Normative Theory of Synaptic Depression. NIPS 2009: 1464-1472 - 2007
- [c6]Máté Lengyel, Peter Dayan:
Hippocampal Contributions to Control: The Third Way. NIPS 2007: 889-896 - 2006
- [c5]Máté Lengyel, Peter Dayan:
Uncertainty, phase and oscillatory hippocampal recall. NIPS 2006: 833-840 - 2005
- [j7]Máté Lengyel, Zsófia Huhn, Péter Érdi:
Computational theories on the function of theta oscillations. Biol. Cybern. 92(6): 393-408 (2005) - [j6]Zsófia Huhn, Máté Lengyel, Gergo Orbán, Péter Érdi:
Dendritic spiking accounts for rate and phase coding in a biophysical model of a hippocampal place cell. Neurocomputing 65-66: 331-341 (2005) - [c4]Gergo Orbán, József Fiser, Richard N. Aslin, Máté Lengyel:
Bayesian model learning in human visual perception. NIPS 2005: 1043-1050 - 2004
- [j5]Gergely Papp, Zsófia Huhn, Máté Lengyel, Péter Érdi:
Effect of dendritic location and different components of LTP expression on the bursting activity of hippocampal CA1 pyramidal cells. Neurocomputing 58-60: 691-697 (2004) - [j4]Máté Lengyel, Péter Érdi:
Theta-modulated feedforward network generates rate and phase coded firing in the entorhino-hippocampal system. IEEE Trans. Neural Networks 15(5): 1092-1099 (2004) - [c3]Máté Lengyel, Peter Dayan:
Rate- and Phase-coded Autoassociative Memory. NIPS 2004: 769-776 - 2001
- [j3]Gergo Orbán, Tamás Kiss, Máté Lengyel, Péter Érdi:
Hippocampal rhythm generation: Gamma-related theta-frequency resonance in CA3 interneurons. Biol. Cybern. 84(2): 123-132 (2001) - [j2]Tamás Kiss, Gergo Orbán, Máté Lengyel, Péter Érdi:
Intrahippocampal gamma and theta rhythm generation in a network model of inhibitory interneurons. Neurocomputing 38-40: 713-719 (2001) - [c2]Fanni Misják, Máté Lengyel, Péter Érdi:
Episodic Memory and Cognitive Map in a Rate Model Network of the Rat Hippocampus. ICANN 2001: 1135-1140
1990 – 1999
- 1999
- [j1]Máté Lengyel, Ádám Kepecs, Péter Érdi:
Location-dependent differences between somatic and dendritic IPSPs. Neurocomputing 26-27: 193-197 (1999) - 1998
- [c1]Péter Érdi, Ádám Kepecs, Máté Lengyel, Klaus Obermayer, Zoltán Szatmáry:
Dynamics of the Hippocampus: Multiple Strategies. ICONIP 1998: 777-780
Coauthor Index
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