CONSEL: for assessing the confidence of phylogenetic tree selection. - Hidetoshi Shimodaira; Masami Hasegawa (Bioinform., 2001)

Parallelization of Phylogenetic Tree Inference Using Grid Technologies. - Yo Yamamoto; Hidemoto Nakada; Hidetoshi Shimodaira; Satoshi Matsuoka (LSGRID, 2004)

Pvclust: an R package for assessing the uncertainty in hierarchical clustering. - Ryota Suzuki 005; Hidetoshi Shimodaira (Bioinform., 2006)

On Scale-Free Prior Distributions and Their Applicability in Large-Scale Network Inference with Gaussian Graphical Models. - Paul Sheridan; Takeshi Kamimura; Hidetoshi Shimodaira (Complex (1), 2009)

Assessing Statistical Reliability of LiNGAM via Multiscale Bootstrap. - Yusuke Komatsu; Shohei Shimizu; Hidetoshi Shimodaira (ICANN (3), 2010)

Multiscale Bagging and Its Applications. - Hidetoshi Shimodaira; Takafumi Kanamori; Masayoshi Aoki; Kouta Mine (IEICE Trans. Inf. Syst., 2011)

Nonparametric Estimation of the Preferential Attachment Function in Complex Networks: Evidence of Deviations from Log Linearity. - Thong Pham; Paul Sheridan; Hidetoshi Shimodaira (ECCS, 2014)

A simple coding for cross-domain matching with dimension reduction via spectral graph embedding. - Hidetoshi Shimodaira (CoRR, 2014)

Special issue on Model Selection and High Dimensional Data Reduction. - S. Ejaz Ahmed; Gerda Claeskens; Hidetoshi Shimodaira; Stefan Van Aelst (Comput. Stat. Data Anal., 2014)

Higher-order accuracy of multiscale-double bootstrap for testing regions. - Hidetoshi Shimodaira (J. Multivar. Anal., 2014)

Cross-Lingual Word Representations via Spectral Graph Embeddings. - Takamasa Oshikiri; Kazuki Fukui; Hidetoshi Shimodaira (ACL (2), 2016)

Image and tag retrieval by leveraging image-group links with multi-domain graph embedding. - Kazuki Fukui; Akifumi Okuno; Hidetoshi Shimodaira (ICIP, 2016)

Cross-validation of matching correlation analysis by resampling matching weights. - Hidetoshi Shimodaira (Neural Networks, 2016)

Spectral Graph-Based Method of Multimodal Word Embedding. - Kazuki Fukui; Takamasa Oshikiri; Hidetoshi Shimodaira (TextGraphs@ACL, 2017)

PAFit: An R Package for Modeling and Estimating Preferential Attachment and Node Fitness in Temporal Complex Networks. - Thong Pham; Paul Sheridan; Hidetoshi Shimodaira (CoRR, 2017)

Word-like character n-gram embedding. - Geewook Kim; Kazuki Fukui; Hidetoshi Shimodaira (NUT@EMNLP, 2018)

A probabilistic framework for multi-view feature learning with many-to-many associations via neural networks. - Akifumi Okuno; Tetsuya Hada; Hidetoshi Shimodaira (ICML, 2018)

On representation power of neural network-based graph embedding and beyond. - Akifumi Okuno; Hidetoshi Shimodaira (CoRR, 2018)

Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability. - Akifumi Okuno; Geewook Kim; Hidetoshi Shimodaira (AISTATS, 2019)

Robust Graph Embedding with Noisy Link Weights. - Akifumi Okuno; Hidetoshi Shimodaira (AISTATS, 2019)

Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities. - Geewook Kim; Akifumi Okuno; Kazuki Fukui; Hidetoshi Shimodaira (IJCAI, 2019)

Segmentation-free compositional n-gram embedding. - Geewook Kim; Kazuki Fukui; Hidetoshi Shimodaira (NAACL-HLT (1), 2019)

An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis. - Shinpei Imori; Hidetoshi Shimodaira (Entropy, 2019)

More Powerful Selective Kernel Tests for Feature Selection. - Jen Ning Lim; Makoto Yamada; Wittawat Jitkrittum; Yoshikazu Terada; Shigeyuki Matsui; Hidetoshi Shimodaira (AISTATS, 2020)

Extrapolation Towards Imaginary 0-Nearest Neighbour and Its Improved Convergence Rate. - Akifumi Okuno; Hidetoshi Shimodaira (NeurIPS, 2020)

Stochastic Neighbor Embedding of Multimodal Relational Data for Image-Text Simultaneous Visualization. - Morihiro Mizutani; Akifumi Okuno; Geewook Kim; Hidetoshi Shimodaira (CoRR, 2020)

Joint estimation of non-parametric transitivity and preferential attachment functions in scientific co-authorship networks. - Masaaki Inoue; Thong Pham; Hidetoshi Shimodaira (J. Informetrics, 2020)

Hyperlink regression via Bregman divergence. - Akifumi Okuno; Hidetoshi Shimodaira (Neural Networks, 2020)

Non-parametric estimation of the preferential attachment function from one network snapshot. - Thong Pham; Paul Sheridan; Hidetoshi Shimodaira (J. Complex Networks, 2021)

Nonparametric estimation of the preferential attachment function from one network snapshot. - Thong Pham; Paul Sheridan; Hidetoshi Shimodaira (CoRR, 2021)

Revisiting Additive Compositionality: AND, OR and NOT Operations with Word Embeddings. - Masahiro Naito; Sho Yokoi; Geewook Kim; Hidetoshi Shimodaira (CoRR, 2021)

Improving Nonparametric Classification via Local Radial Regression with an Application to Stock Prediction. - Ruixing Cao; Akifumi Okuno; Kei Nakagawa; Hidetoshi Shimodaira (CoRR, 2021)

A Hypergraph Approach for Estimating Growth Mechanisms of Complex Networks. - Masaaki Inoue; Thong Pham; Hidetoshi Shimodaira (IEEE Access, 2022)

Norm of Word Embedding Encodes Information Gain. - Momose Oyama; Sho Yokoi; Hidetoshi Shimodaira (EMNLP, 2023)

Discovering Universal Geometry in Embeddings with ICA. - Hiroaki Yamagiwa; Momose Oyama; Hidetoshi Shimodaira (EMNLP, 2023)

Improving word mover's distance by leveraging self-attention matrix. - Hiroaki Yamagiwa; Sho Yokoi; Hidetoshi Shimodaira (EMNLP (Findings), 2023)

Knowledge Sanitization of Large Language Models. - Yoichi Ishibashi; Hidetoshi Shimodaira (CoRR, 2023)

Shimo Lab at "Discharge Me!": Discharge Summarization by Prompt-Driven Concatenation of Electronic Health Record Sections. - Yunzhen He; Hiroaki Yamagiwa; Hidetoshi Shimodaira (BioNLP@ACL, 2024)

3D Rotation and Translation for Hyperbolic Knowledge Graph Embedding. - Yihua Zhu 002; Hidetoshi Shimodaira (EACL (1), 2024)

Block-Diagonal Orthogonal Relation and Matrix Entity for Knowledge Graph Embedding. - Yihua Zhu 002; Hidetoshi Shimodaira (EMNLP (Findings), 2024)

Understanding Higher-Order Correlations Among Semantic Components in Embeddings. - Momose Oyama; Hiroaki Yamagiwa; Hidetoshi Shimodaira (EMNLP, 2024)

Axis Tour: Word Tour Determines the Order of Axes in ICA-transformed Embeddings. - Hiroaki Yamagiwa; Yusuke Takase; Hidetoshi Shimodaira (EMNLP (Findings), 2024)

Zipfian Whitening. - Sho Yokoi; Han Bao 002; Hiroto Kurita; Hidetoshi Shimodaira (NeurIPS, 2024)

Predicting Drug-Gene Relations via Analogy Tasks with Word Embeddings. - Hiroaki Yamagiwa; Ryoma Hashimoto; Kiwamu Arakane; Ken Murakami; Shou Soeda; Momose Oyama; Mariko Okada; Hidetoshi Shimodaira (CoRR, 2024)

Quantifying Lexical Semantic Shift via Unbalanced Optimal Transport. - Ryo Kishino; Hiroaki Yamagiwa; Ryo Nagata; Sho Yokoi; Hidetoshi Shimodaira (ACL (1), 2025)

Mapping 1, 000+ Language Models via the Log-Likelihood Vector. - Momose Oyama; Hiroaki Yamagiwa; Yusuke Takase; Hidetoshi Shimodaira (ACL (1), 2025)

Revisiting Cosine Similarity via Normalized ICA-transformed Embeddings. - Hiroaki Yamagiwa; Momose Oyama; Hidetoshi Shimodaira (COLING, 2025)

Norm of Mean Contextualized Embeddings Determines their Variance. - Hiroaki Yamagiwa; Hidetoshi Shimodaira (COLING, 2025)

Mapping 1,000+ Language Models via the Log-Likelihood Vector. - Momose Oyama; Hiroaki Yamagiwa; Yusuke Takase; Hidetoshi Shimodaira (CoRR, 2025)

DeLTa: A Decoding Strategy based on Logit Trajectory Prediction Improves Factuality and Reasoning Ability. - Yunzhen He; Yusuke Takase; Yoichi Ishibashi; Hidetoshi Shimodaira (CoRR, 2025)

Beyond Chains: Bridging Large Language Models and Knowledge Bases in Complex Question Answering. - Yihua Zhu; Qianying Liu; Akiko Aizawa; Hidetoshi Shimodaira (CoRR, 2025)

Revealing Language Model Trajectories via Kullback-Leibler Divergence. - Ryo Kishino; Yusuke Takase; Momose Oyama; Hiroaki Yamagiwa; Hidetoshi Shimodaira (CoRR, 2025)

Likelihood Variance as Text Importance for Resampling Texts to Map Language Models. - Momose Oyama; Ryo Kishino; Hiroaki Yamagiwa; Hidetoshi Shimodaira (CoRR, 2025)