Seuraa
Ryota Kobayashi
Ryota Kobayashi
The University of Tokyo
Vahvistettu sähköpostiosoite verkkotunnuksessa k.u-tokyo.ac.jp - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold
R Kobayashi, Y Tsubo, S Shinomoto
Frontiers in computational neuroscience 3, 762, 2009
2402009
TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics
R Kobayashi, R Lambiotte
ICWSM' 2016, 191-200, 2016
2322016
A benchmark test for a quantitative assessment of simple neuron models
R Jolivet, R Kobayashi, A Rauch, R Naud, S Shinomoto, W Gerstner
Journal of neuroscience methods 169 (2), 417-424, 2008
1882008
Reconstructing neuronal circuitry from parallel spike trains
R Kobayashi, S Kurita, A Kurth, K Kitano, K Mizuseki, M Diesmann, ...
Nature communications 10 (1), 4468, 2019
1022019
Modeling the spread of fake news on Twitter
T Murayama, S Wakamiya, E Aramaki, R Kobayashi
Plos one 16 (4), e0250419, 2021
942021
Estimation of time-dependent input from neuronal membrane potential
R Kobayashi, S Shinomoto, P Lansky
Neural Computation 23 (12), 3070-3093, 2011
382011
Impact of network topology on inference of synaptic connectivity from multi-neuronal spike data simulated by a large-scale cortical network model.
R Kobayashi, K Kitano
Journal of computational neuroscience, 2013
372013
Impact of slow K+ currents on spike generation can be described by an adaptive threshold model
R Kobayashi, K Kitano
Journal of computational neuroscience 40, 347-362, 2016
302016
Predicting the success of online petitions leveraging multidimensional time-series
J Proskurnia, P Grabowicz, R Kobayashi, C Castillo, P Cudré-Mauroux, ...
Proceedings of the 26th International Conference on World Wide Web, 755-764, 2017
272017
State space method for predicting the spike times of a neuron
R Kobayashi, S Shinomoto
Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 75 (1 …, 2007
262007
Analyzing temporal patterns of topic diversity using graph clustering
T Hashimoto, DL Shepard, T Kuboyama, K Shin, R Kobayashi, T Uno
The Journal of Supercomputing 77, 4375-4388, 2021
252021
Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth
M Levakova, L Kostal, C Monsempès, P Lucas, R Kobayashi
Journal of the Royal Society Interface 16 (157), 20190246, 2019
232019
Evolution of public opinion on COVID-19 vaccination in Japan: large-scale Twitter data analysis
R Kobayashi, Y Takedomi, Y Nakayama, T Suda, T Uno, T Hashimoto, ...
Journal of Medical Internet Research 24 (12), e41928, 2022
212022
Input-output relationship in social communications characterized by spike train analysis
T Aoki, T Takaguchi, R Kobayashi, R Lambiotte
Physical Review E 94 (4), 042313, 2016
212016
Optimal decoding and information transmission in Hodgkin–Huxley neurons under metabolic cost constraints
L Kostal, R Kobayashi
Biosystems 136, 3-10, 2015
212015
An extended Hilbert transform method for reconstructing the phase from an oscillatory signal
A Matsuki, H Kori, R Kobayashi
Scientific Reports 13 (1), 3535, 2023
192023
Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron
R Kobayashi, Y Tsubo, P Lansky, S Shinomoto
Advances in Neural Information Processing Systems 24, 2011
192011
Estimation of excitatory and inhibitory synaptic conductance variations in motoneurons during locomotor-like rhythmic activity
R Kobayashi, H Nishimaru, H Nishijo
Neuroscience 335, 72-81, 2016
182016
A convolutional neural network for estimating synaptic connectivity from spike trains
D Endo, R Kobayashi, R Bartolo, BB Averbeck, Y Sugase-Miyamoto, ...
Scientific Reports 11 (1), 12087, 2021
17*2021
Estimating community feedback effect on topic choice in social media with predictive modeling
DI Adelani, R Kobayashi, I Weber, PA Grabowicz
EPJ Data Science 9 (1), 25, 2020
152020
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Artikkelit 1–20