Spatially "Mt. Fuji" Coupled LDPC Codes. - Yuta Nakahara; Shota Saito; Toshiyasu Matsushima (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2017)

A Note on Weight Distributions of Spatially "Mt. Fuji" Coupled LDPC Codes. - Yuta Nakahara; Toshiyasu Matsushima (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2018)

Covariance Evolution for Spatially "Mt. Fuji" Coupled LDPC Codes. - Yuta Nakahara; Toshiyasu Matsushima (ITW, 2019)

A Stochastic Model of Block Segmentation Based on the Quadtree and the Bayes Code for It. - Yuta Nakahara; Toshiyasu Matsushima (DCC, 2020)

Theoretical Analysis of the Advantage of Deepening Neural Networks. - Yasushi Esaki; Yuta Nakahara; Toshiyasu Matsushima (ICMLA, 2020)

Autoregressive Image Generative Models with Normal and t-distributed Noise and the Bayes Codes for Them. - Yuta Nakahara; Toshiyasu Matsushima (ISITA, 2020)

Analysis of Decoding Error Probability of Spatially "Mt. Fuji" Coupled LDPC Codes in Waterfall Region of the BEC. - Yuta Nakahara; Toshiyasu Matsushima (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2020)

Hyperparameter Learning of Stochastic Image Generative Models with Bayesian Hierarchical Modeling and Its Effect on Lossless Image Coding. - Yuta Nakahara; Toshiyasu Matsushima (ITW, 2021)

Meta-Tree Random Forest: Probabilistic Data-Generative Model and Bayes Optimal Prediction. - Nao Dobashi; Shota Saito; Yuta Nakahara; Toshiyasu Matsushima (Entropy, 2021)

A Stochastic Model for Block Segmentation of Images Based on the Quadtree and the Bayes Code for It. - Yuta Nakahara; Toshiyasu Matsushima (Entropy, 2021)

Probability Distribution on Rooted Trees. - Yuta Nakahara; Shota Saito; Akira Kamatsuka; Toshiyasu Matsushima (ISIT, 2022)

Bayes Optimal Estimation and Its Approximation Algorithm for Difference with and without Treatment under URLC Model. - Taisuke Ishiwatari; Shota Saito; Yuta Nakahara; Yuji Iikubo; Toshiyasu Matsushima (ISITA, 2022)

Two-dimensional Autoregressive Model with Time-varying Parameters and the Bayes Codes. - Yuta Nakahara; Toshiyasu Matsushima (ISITA, 2022)

Stochastic 2D Signal Generative Model with Wavelet Packets Basis Regarded as a Random Variable and Bayes Optimal Processing. - Ryohei Oka; Yuta Nakahara; Toshiyasu Matsushima (CoRR, 2022)

Stochastic Model of Block Segmentation Based on Improper Quadtree and Optimal Code under the Bayes Criterion. - Yuta Nakahara; Toshiyasu Matsushima (Entropy, 2022)

Probability Distribution on Full Rooted Trees. - Yuta Nakahara; Shota Saito; Akira Kamatsuka; Toshiyasu Matsushima (Entropy, 2022)

The Ratio of the Desired Parameters of Deep Neural Networks. - Yasushi Esaki; Yuta Nakahara; Toshiyasu Matsushima (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2022)

Hyperparameter Learning of Bayesian Context Tree Models. - Yuta Nakahara; Shota Saito; Koshi Shimada; Toshiyasu Matsushima (ISIT, 2023)

Tree-Structured Gaussian Mixture Models and Their Variational Inference. - Yuta Nakahara (SMC, 2023)

Prediction Algorithms Achieving Bayesian Decision Theoretical Optimality Based on Decision Trees as Data Observation Processes. - Yuta Nakahara; Shota Saito; Naoki Ichijo; Koki Kazama; Toshiyasu Matsushima (CoRR, 2023)

Bayesian Decision-Theoretic Prediction with Ensemble of Meta-Trees for Classification Problems. - Naoki Ichijo; Ryota Maniwa; Yuta Nakahara; Koshi Shimada; Toshiyasu Matsushima (ISITA, 2024)

Variational Bayesian Methods for a Tree-Structured Stick-Breaking Process Mixture of Gaussians by Application of the Bayes Codes for Context Tree Models. - Yuta Nakahara (ISITA, 2024)

An Algorithmic Framework for Constructing Multiple Decision Trees by Evaluating Their Combination Performance Throughout the Construction Process. - Keito Tajima; Naoki Ichijo; Yuta Nakahara; Koshi Shimada; Toshiyasu Matsushima (SMC, 2024)

Boosting-Based Sequential Meta-Tree Ensemble Construction for Improved Decision Trees. - Ryota Maniwa; Naoki Ichijo; Yuta Nakahara; Toshiyasu Matsushima (CoRR, 2024)

An Algorithmic Framework for Constructing Multiple Decision Trees by Evaluating Their Combination Performance Throughout the Construction Process. - Keito Tajima; Naoki Ichijo; Yuta Nakahara; Toshiyasu Matsushima (CoRR, 2024)

Variational Bayesian Methods for a Tree-Structured Stick-Breaking Process Mixture of Gaussians. - Yuta Nakahara (CoRR, 2024)

Batch Updating of a Posterior Tree Distribution Over a Meta-Tree. - Yuta Nakahara; Toshiyasu Matsushima (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2024)

Bayesian Decision Theory on Decision Trees: Uncertainty Evaluation and Interpretability. - Yuta Nakahara; Shota Saito; Naoki Ichijo; Koki Kazama; Toshiyasu Matsushima (AISTATS, 2025)

A Lower Bound for the Number of Linear Regions of Ternary ReLU Regression Neural Networks. - Yuta Nakahara; Manabu Kobayashi; Toshiyasu Matsushima (CoRR, 2025)

Bayes optimal estimation and its approximation algorithm for difference with and without treatment under IRSLC model. - Taisuke Ishiwatari; Shota Saito; Yuta Nakahara; Yuji Iikubo; Toshiyasu Matsushima (Int. J. Data Sci. Anal., 2025)