Multi-Aspect Gene Relation Analysis. - Hiroshi Yamakawa; Koji Maruhashi; Yoshio Nakao; Mutsuyo Yamaguchi (Pacific Symposium on Biocomputing, 2005)

Predicting Types of Protein-Protein Interactions Using a Multiple-Instance Learning Model. - Hiroshi Yamakawa; Koji Maruhashi; Yoshio Nakao (JSAI, 2006)

EigenDiagnostics: Spotting Connection Patterns and Outliers in Large Graphs. - Koji Maruhashi; Christos Faloutsos (ICDM Workshops, 2010)

Metric forensics: a multi-level approach for mining volatile graphs. - Keith Henderson; Tina Eliassi-Rad; Christos Faloutsos; Leman Akoglu; Lei Li 005; Koji Maruhashi; B. Aditya Prakash; Hanghang Tong (KDD, 2010)

MultiAspectForensics: Pattern Mining on Large-Scale Heterogeneous Networks with Tensor Analysis. - Koji Maruhashi; Fan Guo 006; Christos Faloutsos (ASONAM, 2011)

EigenSP: A More Accurate Shortest Path Distance Estimation on Large-Scale Networks. - Koji Maruhashi; Junichi Shigezumi; Nobuhiro Yugami; Christos Faloutsos (ICDM Workshops, 2012)

MultiAspectForensics: mining large heterogeneous networks using tensor. - Koji Maruhashi; Fan Guo 006; Christos Faloutsos (Int. J. Web Eng. Technol., 2012)

MultiAspectSpotting: Spotting Anomalous Behavior within Count Data Using Tensor. - Koji Maruhashi; Nobuhiro Yugami (PAKDD (2), 2014)

TOPASE: Detection of brute force attacks used disciplined IPs from IDS log. - Satomi Honda; Yuki Unno; Koji Maruhashi; Masahiko Takenaka; Satoru Torii (IM, 2015)

TOPASE: Detection and Prevention of Brute Force Attacks with Disciplined IPs from IDS Logs. - Satomi Saito; Koji Maruhashi; Masahiko Takenaka; Satoru Torii (J. Inf. Process., 2016)

Learning Multi-Way Relations via Tensor Decomposition With Neural Networks. - Koji Maruhashi; Masaru Todoriki; Takuya Ohwa; Keisuke Goto 001; Yu Hasegawa; Hiroya Inakoshi; Hirokazu Anai (AAAI, 2018)

Linear Tensor Projection Revealing Nonlinearity. - Koji Maruhashi; Heewon Park; Rui Yamaguchi; Satoru Miyano (CoRR, 2020)

Semi-Automatic Reliable Explanations for Prediction in Graphs. - Masaru Todoriki; Masafumi Shingu; Shotaro Yano; Arseny Tolmachev; Tao Komikado; Koji Maruhashi (CCWC, 2021)

Graph-based Massive Open Online Course (MOOC) Dropout Prediction using Clickstream Data in Virtual Learning Environment. - Izumi Nitta; Ryo Ishizaki; Masafumi Shingu; Satoshi Nakashima; Koji Maruhashi; Arseny Tolmachev; Masaru Todoriki (ICCSE, 2021)

Crowdsourcing Evaluation of Saliency-Based XAI Methods. - Xiaotian Lu; Arseny Tolmachev; Tatsuya Yamamoto; Koh Takeuchi 001; Seiji Okajima; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima (ECML/PKDD (5), 2021)

Inter-domain Multi-relational Link Prediction. - Luu Huu Phuc; Koh Takeuchi 001; Seiji Okajima; Arseny Tolmachev; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima (ECML/PKDD (2), 2021)

Bermuda Triangles: GNNs Fail to Detect Simple Topological Structures. - Arseny Tolmachev; Akira Sakai; Masaru Todoriki; Koji Maruhashi (CoRR, 2021)

Generating 3D Molecules for Target Protein Binding. - Meng Liu 015; Youzhi Luo; Kanji Uchino; Koji Maruhashi; Shuiwang Ji (ICML, 2022)

Incorporating AI Methods in Micro-dynamic Analysis to Support Group-Specific Policy-Making. - Shuang Chang; Tatsuya Asai; Yusuke Koyanagi; Kento Uemura; Koji Maruhashi; Kotaro Ohori (PRIMA, 2022)

High-Dimensional Causal Discovery: Learning from Inverse Covariance via Independence-based Decomposition. - Shuyu Dong; Kento Uemura; Akito Fujii; Shuang Chang; Yusuke Koyanagi; Koji Maruhashi; Michèle Sebag (CoRR, 2022)

Automated Data Augmentations for Graph Classification. - Youzhi Luo; Michael McThrow; Wing Yee Au 002; Tao Komikado; Kanji Uchino; Koji Maruhashi; Shuiwang Ji (ICLR, 2023)

A Latent Diffusion Model for Protein Structure Generation. - Cong Fu 003; Keqiang Yan; Limei Wang; Wing Yee Au 002; Michael McThrow; Tao Komikado; Koji Maruhashi; Kanji Uchino; Xiaoning Qian; Shuiwang Ji (LoG, 2023)

An Iterative Analysis Method Using Causal Discovery Algorithms to Enhance ABM as a Policy Tool. - Shuang Chang; Takashi Kato; Yusuke Koyanagi; Kento Uemura; Koji Maruhashi (WSC, 2023)

Subgrouping Causal Networks of Disease Onset in Large-scale Health and Medical Data using Supercomputer Fugaku. - Taisei Tosaki; Eiichiro Uchino; Yohei Harada; Minoru Sakuragi; Yusuke Koyanagi; Seiji Okajima; Hirofumi Suzuki; Kentaro Kanamori; Masahiro Asaoka; Kouji Kurihara; Takuya Takagi; Koji Maruhashi; et al. (BIBM, 2024)

Causal-Based Rack Layout Optimization in Retail: Incorporating Agent-Based Modeling and Causal Discovery. - Shuang Chang; Shohei Yamane; Koji Maruhashi (WSC, 2024)

DCDILP: a distributed learning method for large-scale causal structure learning. - Shuyu Dong; Michèle Sebag; Kento Uemura; Akito Fujii; Shuang Chang; Yusuke Koyanagi; Koji Maruhashi (CoRR, 2024)

DCILP: A Distributed Approach for Large-Scale Causal Structure Learning. - Shuyu Dong; Michèle Sebag; Kento Uemura; Akito Fujii; Shuang Chang; Yusuke Koyanagi; Koji Maruhashi (AAAI, 2025)

Long-term care comparative studies by agent-based simulation: a computational framework and a case study. - Shuang Chang; Koji Maruhashi (J. Comput. Soc. Sci., 2025)