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ORCIDTakeru Matsuda
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2020 – today
- 2024
[j15]Naoki Marumo
, Takeru Matsuda, Yuto Miyatake:
Modelling the discretization error of initial value problems using the Wishart distribution. Appl. Math. Lett. 147: 108833 (2024)- [j14]Xiao Li, Takeru Matsuda, Fumiyasu Komaki:
Empirical Bayes Poisson matrix completion. Comput. Stat. Data Anal. 197: 107976 (2024) - [j13]Takeru Matsuda:
Adapting to General Quadratic Loss via Singular Value Shrinkage. IEEE Trans. Inf. Theory 70(5): 3640-3657 (2024) - [c7]Rongzhi Li, Takeru Matsuda, Hitomi Yanaka:
Exploring Intra and Inter-language Consistency in Embeddings with ICA. EMNLP 2024: 19104-19111 - [i14]Rongzhi Li, Takeru Matsuda, Hitomi Yanaka:
Exploring Intra and Inter-language Consistency in Embeddings with ICA. CoRR abs/2406.12474 (2024) - [i13]Takeru Matsuda, Yuji Nakatsukasa:
Polynomial approximation of noisy functions. CoRR abs/2410.02317 (2024) - 2023
- [i12]Naoki Marumo, Takeru Matsuda, Yuto Miyatake:
Modelling the discretization error of initial value problems using the Wishart distribution. CoRR abs/2306.04084 (2023) - 2022
- [j12]Takeru Matsuda, Fumitaka Homae, Hama Watanabe, Gentaro Taga, Fumiyasu Komaki:
Oscillator decomposition of infant fNIRS data. PLoS Comput. Biol. 18(3) (2022) - 2021
- [j11]Takeru Matsuda, Yuto Miyatake:
Generalization of partitioned Runge-Kutta methods for adjoint systems. J. Comput. Appl. Math. 388: 113308 (2021) - [j10]Takeru Matsuda, Masatoshi Uehara, Aapo Hyvärinen:
Information criteria for non-normalized models. J. Mach. Learn. Res. 22: 158:1-158:33 (2021) - [j9]Takeru Matsuda, Yuto Miyatake:
Estimation of Ordinary Differential Equation Models with Discretization Error Quantification. SIAM/ASA J. Uncertain. Quantification 9(1): 302-331 (2021) - [c6]Shun-ichi Amari, Takeru Matsuda:
Wasserstein Statistics in One-Dimensional Location-Scale Models. GSI 2021: 499-506 - [c5]Wenkai Xu, Takeru Matsuda:
Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold. ICML 2021: 11502-11513 - [i11]Takeru Matsuda, Yuto Miyatake:
Generalized nearly isotonic regression. CoRR abs/2108.13010 (2021) - 2020
- [c4]Wenkai Xu, Takeru Matsuda:
A Stein Goodness-of-fit Test for Directional Distributions. AISTATS 2020: 320-330 - [c3]Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda:
A Unified Statistically Efficient Estimation Framework for Unnormalized Models. AISTATS 2020: 809-819 - [c2]Masatoshi Uehara, Takeru Matsuda, Jae Kwang Kim:
Imputation estimators for unnormalized models with missing data. AISTATS 2020: 831-841 - [i10]Takeru Matsuda, Yuto Miyatake:
Generalization of partitioned Runge-Kutta methods for adjoint systems. CoRR abs/2003.09789 (2020) - [i9]Takeru Matsuda, Tasuku Soma:
Information geometry of operator scaling. CoRR abs/2005.01453 (2020)
2010 – 2019
- 2019
- [j8]Takeru Matsuda, Fumiyasu Komaki:
Empirical Bayes matrix completion. Comput. Stat. Data Anal. 137: 195-210 (2019) - [j7]Takeru Matsuda, William E. Strawderman:
Improved loss estimation for a normal mean matrix. J. Multivar. Anal. 169: 300-311 (2019) - [j6]Yuzo Maruyama, Takeru Matsuda, Toshio Ohnishi:
Harmonic Bayesian Prediction Under $\alpha$ -Divergence. IEEE Trans. Inf. Theory 65(9): 5352-5366 (2019) - [c1]Takeru Matsuda, Aapo Hyvärinen:
Estimation of Non-Normalized Mixture Models. AISTATS 2019: 2555-2563 - [i8]Masatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda:
Unified estimation framework for unnormalized models with statistical efficiency. CoRR abs/1901.07710 (2019) - [i7]Masatoshi Uehara, Takeru Matsuda, Jae Kwang Kim:
Imputation estimators for unnormalized models with missing data. CoRR abs/1903.03630 (2019) - [i6]Takeru Matsuda, Masatoshi Uehara, Aapo Hyvärinen:
Information criteria for non-normalized models. CoRR abs/1905.05976 (2019) - [i5]Takeru Matsuda, Yuto Miyatake:
Estimation of ordinary differential equation models with discretization error quantification. CoRR abs/1907.10565 (2019) - [i4]Shin-Ichi Ito, Takeru Matsuda, Yuto Miyatake:
Adjoint-based exact Hessian-vector multiplication using symplectic Runge-Kutta methods. CoRR abs/1910.06524 (2019) - 2018
- [i3]Takeru Matsuda, Aapo Hyvärinen:
Estimation of Non-Normalized Mixture Models and Clustering Using Deep Representation. CoRR abs/1805.07516 (2018) - [i2]Takeru Matsuda, Akimichi Takemura:
Game-theoretic derivation of upper hedging prices of multivariate contingent claims and submodularity. CoRR abs/1806.07626 (2018) - [i1]Masatoshi Uehara, Takeru Matsuda, Fumiyasu Komaki:
Analysis of Noise Contrastive Estimation from the Perspective of Asymptotic Variance. CoRR abs/1808.07983 (2018) - 2017
- [j5]Takayuki Koyama, Takeru Matsuda, Fumiyasu Komaki:
Minimax Estimation of Quantum States Based on the Latent Information Priors. Entropy 19(11): 618 (2017) - [j4]Takeru Matsuda, Fumiyasu Komaki:
Time Series Decomposition into Oscillation Components and Phase Estimation. Neural Comput. 29(2): 332-367 (2017) - [j3]Takeru Matsuda, Fumiyasu Komaki:
Multivariate Time Series Decomposition into Oscillation Components. Neural Comput. 29(8): 2055-2075 (2017) - [j2]Takeru Matsuda, Keiichi Kitajo, Yoko Yamaguchi, Fumiyasu Komaki:
A point process modeling approach for investigating the effect of online brain activity on perceptual switching. NeuroImage 152: 50-59 (2017) - 2013
- [j1]Takeru Matsuda, Takayasu Matsuo:
A new geometric integration approach based on local invariants. JSIAM Lett. 5: 37-40 (2013)
Coauthor Index
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