Masahiro Suzuki, Takaaki Kaneko, Yutaka Matsuo: Pixyz: a Python library for developing deep generative models, Advanced Robotics, (2023).
Tadahiro Taniguchi, Shingo Murata, Masahiro Suzuki, Dimitri Ognibene, Pablo Lanillos, Emre Ugur, Lorenzo Jamone, Tomoaki Nakamura, Alejandra Ciria, Bruno Lara, Giovanni Pezzulo: World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges, Advanced Robotics, (2023).
Takeshi Kojima, Yusuke Iwasawa, Yutaka Matsuo: Robustifying Vision Transformer Without Retraining From Scratch Using Attention Based Test-Time Adaptation, New Generation Computing, (2022).[paper]
Fukuchi, Y., Osawa, M., Yamakawa, H., & Imai, M. Explaining Intelligent Agent amp;#x2019;s Future Motion on Basis of Vocabulary Learning With Human Goal Inference. IEEE Access, 10, 54336–54347. (2022).[paper]
Hitoshi Nakanishi, Masahiro Suzuki, Yutaka Matuo. Fixing the train-test objective discrepancy: Iterative Image Inpainting for Unsupervised Anomaly Detection, J-Stage in August Vol.30, (2022).
Taniguchi, A., Fukawa, A., & Yamakawa, H. Hippocampal formation-inspired probabilistic generative model. Neural Networks: The Official Journal of the International Neural Network Society.(2022). [paper]
Taniguchi, T., Yamakawa, H., Nagai, T., Doya, K., Sakagami, M., Suzuki, M., Nakamura, T., & Taniguchi, A. A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots. Neural Networks: The Official Journal of the International Neural Network Society.(2022). [paper]
Fukuchi, Y., Osawa, M., Yamakawa, H., Takahashi, T., & Imai, M. Conveying Intention by Motions With Awareness of Information Asymmetry. Frontiers in Robotics and AI, 9. (2022). [paper]
Wataru Kumagai, Akiyoshi Sannai, Makoto Kawano: Universal Approximation with Neural Networks on Function Spaces, Journal of Experimental & Theoretical Artificial Intelligence.(2022).
Masahiro Suzuki, Yutaka Matsuo: A survey of multimodal deep generative models, Advanced Robotics.(2022). [paper]
Kei Akuzawa, Yusuke Iwasawa, Yutaka Matsuo. “Information-theoretic regularization for learning global features by sequential VAE”, Mach Learn (2021). [paper]
Hiroshi Yamakawa: The whole brain architecture approach: Accelerating the development of artificial general intelligence by referring to the brain, Neural Networks (2021). [paper]
Seiya Sato & Hiroshi Yamakawa: Bypassing combinatorial explosions in equivalence structure extraction. Knowledge and Information Systems (2021) [paper]
Tatsuya Matsushima, Naruya Kondo, Yusuke Iwasawa, Kaoru Nasuno, Yutaka Matsuo: Modeling Task Uncertainty for Safe Meta-imitation Learning, Frontiers in Robotics and AI, Vol. 7, pp.189,(2020).[paper]
Keiichi Ochiai, Yusuke Fukazawa, Wataru Yamada, Hiroyuki Manabe, Yutaka Matsuo: Gravity of Location-based Service: Analyzing the Effects for Mobility Pattern and Location Prediction, Proceedings of the International AAAI Conference on Web and Social Media, 14(1), pp.476-487 (2020).[paper]
Hiroshi Yamakawa: Revealing the computational meaning of neocortical interarea signals. Frontiers in Computational Neuroscience, Vol.14, No.74 (2020).[paper]
Masaaki Sato, Kotaro Mizuta, Tanvir Islam, Masako Kawano, Yukiko Sekine, Takashi Takekawa, Daniel Gomez-Dominguez, Alexander Schmidt, Fred Wolf, Karam Kim, Hiroshi Yamakawa, Masamichi Ohkura, Min Goo Lee, Tomoki Fukai, Junichi Nakai, Yasunori Hayashi: Distinct mechanisms of over-representation of landmarks and rewards in the hippocampus, Cell Reports, (2020)[paper]
Tadahiro Taniguchi, Tomoaki Nakamura, Masahiro Suzuki, Ryo Kuniyasu, Kaede Hayashi, Akira Taniguchi, Takato Horii & Takayuki Nagai, Neuro-SERKET: Development of Integrative Cognitive System Through the Composition of Deep Probabilistic Generative Models, New Generation Computing, (2020).[paper]
Hiroshi Yamakawa:, Attentional Reinforcement Learning in the Brain, New Generation Computing, doi:10.1007/s00354-019-00081-z, (2020).[paper]
Matsuda N, Matsuo Y: Impact of MBA on Entrepreneurial Success:Do Entrepreneurs Acquire Capacity through the Program or Does MBA Only Signal Gifted Talent and Experience?, Journal of Entrepreneurship & Organization Management,Vol. 6, No. 1, pp. 211 (2017).[paper]
N. Matsuda, Y. Matsuo: Governing Board Interlocks As An Indicator Of IPO, Corporate Board: Role, Duties and Composition, Vol. 12, Issue 3 (2016).[paper]
Yusuke Iwasawa, Ikuko Yairi, Yutaka Matsuo: Combining Human Action Sensing of Wheelchair Users and Machine Learning for Autonomous Accessibility Data Collection, IEICE Transactions, Vol. E99-D, No. 4, pp. 1153-1161 (2016).[paper]
Takeshi Sakaki, Makoto Okazaki, Yutaka Matsuo: Tweet analysis for realtime event detection and earthquake reporting system development, IEEE Transactions on Knowledge and Data Engineering, Vol. 25, No. 4, pp. 919, 931 (2013).[paper]
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka: Minimally Supervised Novel Relation Extraction Using a Latent Relational Mapping, IEEE Transaction on Knowledge and Data Engineering, Vol. 25, No. 2, pp. 419-432 (2013).[paper]
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka: Automatic Annotation of Ambiguous Personal Names on the Web, Computational Intelligence, Vol. 28, No. 3, pp. 398-425 (2012).[paper]
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka: Measuring the Degree of Synonymy between Words Using Relational Similarity between Word Pairs as a Proxy, IEICE Transactions, Vol. 95-D, No. 8, pp. 2116-2123 (2012).[paper]
Yingzi Jin, Ching-Yung Lin, Yutaka Matsuo, Mitsuru Ishizuka: Mining dynamic social networks from public news articles for company value prediction, Social Network Analysis and Mining Vol. 2, No. 3, pp. 217-228 (2012).[paper]
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka: A Supervised Classification Approach for Measuring Relational Similarity between Word Pairs, IEICE Transactions, Vol. 94-D, No. 11, pp. 2227-2233 (2011).[paper]
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka: Automatic Discovery of Personal Name Aliases from the Web, IEEE Transactions on Knowledge and Data Engineering, Vol. 23, No. 6, pp. 831-844 (2011).[paper]
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka: A Web Search Engine-Based Approach to Measure Semantic Similarity between Words, IEEE Transactions on Knowledge and Data Engineering, Vol. 23, No. 7, pp. 977-990 (2011).[paper]
Haibo Li, Yutaka Matsuo, and Mitsuru Ishizuka: Graph based Multi-View Learning for Semantic Relation Extraction, International Journal of Semantic Computing (2010)
Yulan Yan, Yutaka Matsuo, Mitsuru Ishizuka: A New Shallow Semantic Parser for Describing the Concept Structure of Text, International Journal of Semantic Computing (2009)
Yingzi Jin, Yutaka Matsuo, and Mitsuru Ishizuka: Extracting Inter-Firm Networks from World Wide Web Using General-Purpose Search Engine, Journal of Online Information Review, Vol. 32, No. 2, pp. 196-210 (2008)
Naoaki Okazaki, Yutaka Matsuo, Mitsuru Ishizuka: An Integrated Summarization System with Sentence Extraction on Fragmentary Information and Sentence Ordering Using Precedence Relation, ACM Transactions on Asian Language Information Processing (ACM-TALIP), Vol. 4, No. 3 (2005)[PDF]
Yutaka Matsuo, Mitsuru Ishizuka: Keyword Extraction from a Single Document using Word Co-ocurrence Statistical Information, International Journal on Artificial Intelligence Tools, Vol. 13, No. 1, pp. 157-169 (2004)[PDF]
Naoaki Okazaki, Yutaka Matsuo, Naohiro Matsumura, Mitsuru Ishizuka: Sentence Extraction by Spreading Activation with Refined Similarity Measure, IEICE Transactions on Information and Systems, Vol. E86-D, No. 9, pp. 1687-1694 (2003)[PDF]
Yutaka Matsuo, Yukio Ohsawa, Mitsuru Ishizuka: Average-clicks: A New Measure of Distance on the World Wide Web, Journal of Intelligent Information Systems, Vol. 20, No. 1, pp. 51-62 (2003)[PDF]
Naohiro Matsumura, Yutaka Matsuo, Yukio Ohsawa, Mitsuru Ishizuka: Discovering Emerging Topics from WWW, Journal of Contingencies and Crisis Management, Vol. 10, No. 2, pp. 73-81 (2002)[PDF]
松尾 豊, 大澤 幸生, 石塚 満: Small World構造を用いた文書からのキーワード抽出, 情報処理学会論文誌, Vol. 43, No. 6, pp. 1825-1833 (2002)[PDF]
Mitsuru Ishizuka, Yutaka Matsuo: SL Method for Computing a Near-optimal Solution using Linear and Non-linear Programming in Cost-based Hypothetical Reasoning, Knowledge-Based Systems, Vol. 15, No. 7, pp. 369-376 (2002)[PDF]