Research
研究
研究業績
カテゴリー
研究領域
年
-
Bypassing combinatorial explosions in equivalence structure extraction
Seiya Sato & Hiroshi Yamakawa
Knowledge and Information Systems (2021)
-
行動時刻を考慮した条件付き変分オートエンコーダによる推薦システム
保住純,岩澤有祐,松尾豊
人工知能学会論文誌,Vol. 36,No. 3 (2021)
-
深層ニューラルネットワークによるクラスと幾何変換の同時分類確率を利用した分布外検知
岡本弘野, 鈴木雅大, 松尾豊
情報処理学会論文誌, Vol.62, No.7, pp.1382-1392 (2021)
-
深層ニューラルネットワークの中間層出力を利用した半教師あり分布外検知
岡本弘野, 鈴木雅大, 松尾豊
情報処理学会論文誌, Vol.62, No.4, pp.1142-1151 (2021)
-
Modeling Task Uncertainty for Safe Meta-imitation Learning
Tatsuya Matsushima, Naruya Kondo, Yusuke Iwasawa, Kaoru Nasuno, Yutaka Matsuo
Frontiers in Robotics and AI, Vol. 7, pp.189,(2020)
-
Gravity of Location-based Service: Analyzing the Effects for Mobility Pattern and Location Prediction
Keiichi Ochiai, Yusuke Fukazawa, Wataru Yamada, Hiroyuki Manabe, Yutaka Matsuo
Proceedings of the International AAAI Conference on Web and Social Media, 14(1), pp.476-487 (2020)
-
Revealing the computational meaning of neocortical interarea signals
Hiroshi Yamakawa
Frontiers in Computational Neuroscience, Vol.14, No.74 (2020)
-
Distinct mechanisms of over-representation of landmarks and rewards in the hippocampus
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
Cell Reports, (2020)
-
Neuro-SERKET:Development of Integrative Cognitive System Through the Composition of Deep Probabilistic Generative Models
Tadahiro Taniguchi, Tomoaki Nakamura, Masahiro Suzuki, Ryo Kuniyasu, Kaede Hayashi, Akira Taniguchi, Takato Horii & Takayuki Nagai, Neuro-SERKET
New Generation Computing, (2020)
-
Attentional Reinforcement Learning in the Brain
Hiroshi Yamakawa
New Generation Computing, doi:10.1007/s00354-019-00081-z, (2020)