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Ryota Kobayashi
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2020 – today
- 2024
- [c12]Shoma Tanaka, Ryota Kobayashi, Hiroyuki Nabae, Koichi Suzumori:
Fiber Jamming Mechanism for Back-Stretchable McKibben Muscles. SII 2024: 48-53 - [i7]Zebing Mao, Ryota Kobayashi, Hiroyuki Nabae, Koichi Suzumori:
Large Language Model-empowered multimodal strain sensory system for shape recognition, monitoring, and human interaction of tensegrity. CoRR abs/2406.10264 (2024) - 2023
- [j16]Hayeong Lee, Lubomir Kostal, Ryohei Kanzaki, Ryota Kobayashi:
Spike frequency adaptation facilitates the encoding of input gradient in insect olfactory projection neurons. Biosyst. 223: 104802 (2023) - [j15]Makoto Ohba, Ryota Kobayashi, Chifumi Iseki, Kazukuni Kirii, Daichi Morioka, Koichi Otani, Yasuyuki Ohta, Yukihiko Sonoda, Koji Suzuki, Masafumi Kanoto:
Effect of cerebrospinal fluid area mask correction on 123I-FP-CIT SPECT images in idiopathic normal pressure hydrocephalus. BMC Medical Imaging 23(1): 81 (2023) - [j14]Ryota Kobayashi, Yasuaki Yuda, Kenichi Higuchi:
Highly-Efficient Low-Latency HARQ Built on NOMA for URLLC: Radio Resource Allocation and Transmission Rate Control Aspects. IEICE Trans. Commun. 106(10): 1015-1023 (2023) - [j13]Ryota Kobayashi, Takanori Hara, Yasuaki Yuda, Kenichi Higuchi:
NOMA-Based Highly-Efficient Low-Latency HARQ with Inter-Base Station Cooperation for URLLC. IEICE Trans. Commun. 106(11): 1219-1227 (2023) - [j12]Ryota Kobayashi, Hiroyuki Nabae, Koichi Suzumori:
Large Torsion Thin Artificial Muscles Tensegrity Structure for Twist Manipulation. IEEE Robotics Autom. Lett. 8(3): 1207-1214 (2023) - [j11]Ryota Kobayashi, Hiroyuki Nabae, Koichi Suzumori:
Active-Bending Six-Bar Tensegrity Modular Robot Driven by Thin Artificial Muscles. IEEE Robotics Autom. Lett. 8(11): 7400-7407 (2023) - 2022
- [j10]Ryota Kobayashi, Hiroyuki Nabae, Gen Endo, Koichi Suzumori:
Soft Tensegrity Robot Driven by Thin Artificial Muscles for the Exploration of Unknown Spatial Configurations. IEEE Robotics Autom. Lett. 7(2): 5349-5356 (2022) - [i6]Yuri Nakayama, Yuka Takedomi, Towa Suda, Takeaki Uno, Takako Hashimoto, Masashi Toyoda, Naoki Yoshinaga, Masaru Kitsuregawa, Luis E. C. Rocha, Ryota Kobayashi:
Evolution of the public opinion on COVID-19 vaccination in Japan. CoRR abs/2207.10924 (2022) - 2021
- [j9]Takako Hashimoto, David Lawrence Shepard, Tetsuji Kuboyama, Kilho Shin, Ryota Kobayashi, Takeaki Uno:
Analyzing temporal patterns of topic diversity using graph clustering. J. Supercomput. 77(5): 4375-4388 (2021) - [c11]Takako Hashimoto, Takeaki Uno, Yuka Takedomi, David Lawrence Shepard, Masashi Toyoda, Naoki Yoshinaga, Masaru Kitsuregawa, Ryota Kobayashi:
Two-stage Clustering Method for Discovering People's Perceptions: A Case Study of the COVID-19 Vaccine from Twitter. IEEE BigData 2021: 614-621 - [c10]Ryota Kobayashi, Patrick Gildersleve, Takeaki Uno, Renaud Lambiotte:
Modeling Collective Anticipation and Response on Wikipedia. ICWSM 2021: 315-326 - [c9]Ryota Kobayashi, Yasuaki Yuda, Kenichi Higuchi:
NOMA-Based Highly-Efficient Low-Latency HARQ Method for URLLC. VTC Fall 2021: 1-6 - [i5]David Ifeoluwa Adelani, Ryota Kobayashi, Ingmar Weber, Przemyslaw A. Grabowicz:
Estimating Community Feedback Effect on Topic Choice in Social Media with Predictive Modeling. CoRR abs/2103.04818 (2021) - [i4]Ryota Kobayashi, Patrick Gildersleve, Takeaki Uno, Renaud Lambiotte:
Modeling Collective Anticipation and Response on Wikipedia. CoRR abs/2105.10900 (2021) - 2020
- [j8]David Ifeoluwa Adelani, Ryota Kobayashi, Ingmar Weber, Przemyslaw A. Grabowicz:
Estimating community feedback effect on topic choice in social media with predictive modeling. EPJ Data Sci. 9(1): 25 (2020) - [i3]Taichi Murayama, Shoko Wakamiya, Eiji Aramaki, Ryota Kobayashi:
Modeling and Predicting Fake News Spreading on Twitter. CoRR abs/2007.14059 (2020)
2010 – 2019
- 2019
- [c8]Han Xu, Takahiro Shinozaki, Ryota Kobayashi:
Effective and Stable Neuron Model Optimization Based on Aggregated CMA-ES. ICASSP 2019: 1264-1268 - [c7]Ryota Kobayashi, Ryo Takano, Hiroyuki Sato, Keiki Takadama:
Simultaneous Local Adaptation for Different Local Properties. IES 2019: 216-227 - 2017
- [j7]Ryota Kobayashi, Hiroshi Nishimaru, Hisao Nishijo, Petr Lánský:
A single spike deteriorates synaptic conductance estimation. Biosyst. 161: 41-45 (2017) - [c6]Julia Proskurnia, Przemyslaw A. Grabowicz, Ryota Kobayashi, Carlos Castillo, Philippe Cudré-Mauroux, Karl Aberer:
Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series. WWW 2017: 755-764 - 2016
- [j6]Ryota Kobayashi, Katsunori Kitano:
Impact of slow K+ currents on spike generation can be described by an adaptive threshold model. J. Comput. Neurosci. 40(3): 347-362 (2016) - [c5]Ryota Kobayashi, Renaud Lambiotte:
TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics. ICWSM 2016: 191-200 - [c4]Jun-ichi Imai, Ryota Kobayashi, Kazuya Jinjo, Hirobumi Suzuki, Kazuto Kameda, Shohei Koshikawa, Seiya Takihara:
Interactive Projection System That Always Presents Information within User's View. SCIS&ISIS 2016: 784-789 - [i2]Takaaki Aoki, Taro Takaguchi, Ryota Kobayashi, Renaud Lambiotte:
Input-output relationship in social communications characterized by spike train analysis. CoRR abs/1603.08144 (2016) - [i1]Ryota Kobayashi, Renaud Lambiotte:
TiDeH: Time-Dependent Hawkes Process for Predicting Retweet Dynamics. CoRR abs/1603.09449 (2016) - 2015
- [j5]Lubomir Kostal, Ryota Kobayashi:
Optimal decoding and information transmission in Hodgkin-Huxley neurons under metabolic cost constraints. Biosyst. 136: 3-10 (2015) - [j4]Ryota Kobayashi, Jufang He, Petr Lánský:
Estimation of the synaptic input firing rates and characterization of the stimulation effects in an auditory neuron. Frontiers Comput. Neurosci. 9: 59 (2015) - 2013
- [j3]Ryota Kobayashi, Katsunori Kitano:
Impact of network topology on inference of synaptic connectivity from multi-neuronal spike data simulated by a large-scale cortical network model. J. Comput. Neurosci. 35(1): 109-124 (2013) - [c3]Wataru Ichimura, Sho Kiyoshige, Masahiro Terasaki, Ryota Kobayashi, Genki Kubo, Hiroki Otsuka, Toshio Sudo:
Anti-resonance peak frequency control by variable on-die capacitance. EMC Compo 2013: 171-174 - 2011
- [j2]Ryota Kobayashi, Shigeru Shinomoto, Petr Lánský:
Estimation of Time-Dependent Input from Neuronal Membrane Potential. Neural Comput. 23(12): 3070-3093 (2011) - [c2]Ryota Kobayashi, Yasuhiro Tsubo, Petr Lánský, Shigeru Shinomoto:
Estimating time-varying input signals and ion channel states from a single voltage trace of a neuron. NIPS 2011: 217-225
2000 – 2009
- 2009
- [j1]Ryota Kobayashi, Yasuhiro Tsubo, Shigeru Shinomoto:
Made-to-order spiking neuron model equipped with a multi-timescale adaptive threshold. Frontiers Comput. Neurosci. 3: 9 (2009) - 2006
- [c1]Ryota Kobayashi, Shigeru Shinomoto:
Predicting spike times from subthreshold dynamics of a neuron. NIPS 2006: 721-728
Coauthor Index
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