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Taro Toyoizumi
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2020 – today
- 2024
- [j22]Taro Toyoizumi, DeLiang Wang:
A surge of submissions. Neural Networks 169: 793-794 (2024) - [j21]DeLiang Wang, Mauro Forti, Tongliang Liu, Taro Toyoizumi:
Expansion of the editorial team. Neural Networks 173: 106209 (2024) - [i10]Yuri Kinoshita, Taro Toyoizumi:
A provable control of sensitivity of neural networks through a direct parameterization of the overall bi-Lipschitzness. CoRR abs/2404.09821 (2024) - 2023
- [j20]Zhengqi He
, Taro Toyoizumi:
Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information. Neural Comput. 35(1): 38-57 (2023) - [j19]Taro Toyoizumi, DeLiang Wang:
Another bumper year. Neural Networks 157: 471-472 (2023) - [j18]Taro Toyoizumi, DeLiang Wang:
Announcement of the Neural Networks Best Paper Award. Neural Networks 157: xl (2023) - [i9]Zhengqi He, Taro Toyoizumi:
Causal Graph in Language Model Rediscovers Cortical Hierarchy in Human Narrative Processing. CoRR abs/2311.10431 (2023) - 2022
- [j17]Kenji Doya, Taro Toyoizumi, DeLiang Wang:
Continual growth and a transition. Neural Networks 145: xx-xxi (2022) - [i8]Zhengqi He
Spontaneous Emerging Preference in Two-tower Language Model. CoRR abs/2210.07041 (2022) - 2021
- [j16]Takuya Isomura
Dimensionality reduction to maximize prediction generalization capability. Nat. Mach. Intell. 3(5): 434-446 (2021) - [j15]Takuya Isomura
Publisher Correction: Dimensionality reduction to maximize prediction generalization capability. Nat. Mach. Intell. 3(5): 457 (2021) - [j14]Takuya Isomura
On the Achievability of Blind Source Separation for High-Dimensional Nonlinear Source Mixtures. Neural Comput. 33(6): 1433-1468 (2021) - [j13]Yoshiki Ito
Learning poly-synaptic paths with traveling waves. PLoS Comput. Biol. 17(2) (2021) - [i7]Zhengqi He, Taro Toyoizumi:
An Information-theoretic Progressive Framework for Interpretation. CoRR abs/2101.02879 (2021) - 2020
- [i6]Takuya Isomura, Taro Toyoizumi:
Dimensionality reduction to maximize prediction generalization capability. CoRR abs/2003.00470 (2020)
2010 – 2019
- 2019
- [j12]James Humble
Intrinsic Spine Dynamics Are Critical for Recurrent Network Learning in Models With and Without Autism Spectrum Disorder. Frontiers Comput. Neurosci. 13: 38 (2019) - 2018
- [j11]Christopher L. Buckley
A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback. PLoS Comput. Biol. 14(1) (2018) - [i5]Takuya Isomura, Taro Toyoizumi:
On the achievability of blind source separation for high-dimensional nonlinear source mixtures. CoRR abs/1808.00668 (2018) - 2017
- [i4]Haiping Huang
Reinforced backpropagation improves test performance of deep networks: a toy-model study. CoRR abs/1701.07974 (2017) - [i3]Haiping Huang, Alireza Goudarzi, Taro Toyoizumi:
Redundancy in active paths of deep networks: a random active path model. CoRR abs/1705.00850 (2017) - 2016
- [j10]Milad Lankarany
Simultaneous Bayesian Estimation of Excitatory and Inhibitory Synaptic Conductances by Exploiting Multiple Recorded Trials. Frontiers Comput. Neurosci. 10: 110 (2016) - [i2]Haiping Huang, Taro Toyoizumi:
Unsupervised feature learning from finite data by message passing: discontinuous versus continuous phase transition. CoRR abs/1608.03714 (2016) - 2015
- [j9]Satohiro Tajima
Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. PLoS Comput. Biol. 11(11) (2015) - [i1]Haiping Huang, Taro Toyoizumi:
Advanced Mean Field Theory of Restricted Boltzmann Machine. CoRR abs/1502.00186 (2015) - 2013
- [j8]Milad Lankarany
Inferring trial-to-trial excitatory and inhibitory synaptic inputs from membrane potential using Gaussian mixture Kalman filtering. Frontiers Comput. Neurosci. 7: 109 (2013) - [c2]Milad Lankarany
Blind Deconvolution of Hodgkin-Huxley neuronal model. EMBC 2013: 3941-3944 - 2012
- [j7]Taro Toyoizumi
Nearly Extensive Sequential Memory Lifetime Achieved by Coupled Nonlinear Neurons. Neural Comput. 24(10): 2678-2699 (2012)
2000 – 2009
- 2009
- [j6]Taro Toyoizumi
Mean-Field Approximations for Coupled Populations of Generalized Linear Model Spiking Neurons with Markov Refractoriness. Neural Comput. 21(5): 1203-1243 (2009) - [j5]Julijana Gjorgjieva
Burst-Time-Dependent Plasticity Robustly Guides ON/OFF Segregation in the Lateral Geniculate Nucleus. PLoS Comput. Biol. 5(12) (2009) - 2007
- [j4]Taro Toyoizumi
Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution. Neural Comput. 19(3): 639-671 (2007) - [j3]Yoshiyuki Sato, Taro Toyoizumi
Bayesian Inference Explains Perception of Unity and Ventriloquism Aftereffect: Identification of Common Sources of Audiovisual Stimuli. Neural Comput. 19(12): 3335-3355 (2007) - 2006
- [j2]Taro Toyoizumi
Generalization of the Mean-Field Method for Power-Law Distributions. Int. J. Bifurc. Chaos 16(1): 129-135 (2006) - [j1]Jean-Pascal Pfister
Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning. Neural Comput. 18(6): 1318-1348 (2006) - 2004
- [c1]Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aihara, Wulfram Gerstner:
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model. NIPS 2004: 1409-1416
Coauthor Index
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