Shinsuke Koyama

16 papers Journal 14Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Coarse-Grained Hawkes Processes.
Entropy
Shinsuke Koyama
2021 J jnl
Estimating the time-varying reproduction number of COVID-19 with a state-space method.
PLoS Comput. Biol.
Shinsuke Koyama, Taiki Horie, Shigeru Shinomoto
2019 J jnl
Statistical inference of the rate of RNA polymerase II elongation by total RNA sequencing.
Bioinform.
Yumi Kawamura, Shinsuke Koyama, Ryo Yoshida
2018 J jnl
Identifying exogenous and endogenous activity in social media.
CoRR
Kazuki Fujita, Alexey N. Medvedev, Shinsuke Koyama, Renaud Lambiotte, Shigeru Shinomoto
2018 J jnl
Projection smoothing for continuous and continuous-discrete stochastic dynamic systems.
Signal Process.
Shinsuke Koyama
2015 J jnl
On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.
Neural Comput.
Shinsuke Koyama
2013 J jnl
Information Transmission Using Non-Poisson Regular Firing.
Neural Comput.
Shinsuke Koyama, Takahiro Omi, Robert E. Kass, Shigeru Shinomoto
2012 — conf
Coding efficiency and detectability of rate fluctuations with non-Poisson neuronal firing.
NIPS
Shinsuke Koyama
2012 — conf
Estimating Neural Firing Rates: An Empirical Bayes Approach.
ICONIP (2)
Shinsuke Koyama
2012 J jnl
On the Relation Between Encoding and Decoding of Neuronal Spikes.
Neural Comput.
Shinsuke Koyama
2010 J jnl
A characterization of the time-rescaled gamma process as a model for spike trains.
J. Comput. Neurosci.
Takeaki Shimokawa, Shinsuke Koyama, Shigeru Shinomoto
2010 J jnl
A new look at state-space models for neural data.
J. Comput. Neurosci.
Liam Paninski, Yashar Ahmadian, Daniel Gil Ferreira, Shinsuke Koyama, Kamiar Rahnama Rad, Michael Vidne, Joshua T. Vogelstein, Wei Wu
2010 J jnl
Comparison of brain-computer interface decoding algorithms in open-loop and closed-loop control.
J. Comput. Neurosci.
Shinsuke Koyama, Steven M. Chase, Andrew S. Whitford, Meel Velliste, Andrew B. Schwartz, Robert E. Kass
2010 J jnl
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-space models.
J. Comput. Neurosci.
Shinsuke Koyama, Liam Paninski
2008 J jnl
Spike Train Probability Models for Stimulus-Driven Leaky Integrate-and-Fire Neurons.
Neural Comput.
Shinsuke Koyama, Robert E. Kass
2007 J jnl
Inference of intrinsic spiking irregularity based on the Kullback-Leibler information.
Biosyst.
Shinsuke Koyama, Shigeru Shinomoto