Real-time and proactive navigation via spatio-temporal prediction. - Naonori Ueda; Futoshi Naya; Hitoshi Shimizu; Tomoharu Iwata; Maya Okawa; Hiroshi Sawada (UbiComp/ISWC Adjunct, 2015)

Online Traffic Flow Prediction Using Convolved Bilinear Poisson Regression. - Maya Okawa; Hideaki Kim; Hiroyuki Toda (MDM, 2017)

Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities. - Yusuke Tanaka 002; Tomoharu Iwata; Toshiyuki Tanaka; Takeshi Kurashima; Maya Okawa; Hiroyuki Toda (AAAI, 2019)

Predicting Traffic Accidents with Event Recorder Data. - Yoshiaki Takimoto; Yusuke Tanaka 002; Takeshi Kurashima; Shuhei Yamamoto; Maya Okawa; Hiroyuki Toda (PredictGIS@SIGSPATIAL, 2019)

Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information. - Maya Okawa; Tomoharu Iwata; Takeshi Kurashima; Yusuke Tanaka 002; Hiroyuki Toda; Naonori Ueda (KDD, 2019)

Spatially Aggregated Gaussian Processes with Multivariate Areal Outputs. - Yusuke Tanaka 002; Toshiyuki Tanaka; Tomoharu Iwata; Takeshi Kurashima; Maya Okawa; Yasunori Akagi; Hiroyuki Toda (NeurIPS, 2019)

Marked Temporal Point Processes for Trip Demand Prediction in Bike Sharing Systems. - Maya Okawa; Yusuke Tanaka 002; Takeshi Kurashima; Hiroyuki Toda; Tomohiro Yamada (IEICE Trans. Inf. Syst., 2019)

Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. - Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 002; Hiroyuki Toda; Takeshi Kurashima; Hisashi Kashima (KDD, 2021)

Predicting Opinion Dynamics via Sociologically-Informed Neural Networks. - Maya Okawa; Tomoharu Iwata (KDD, 2022)

Aggregated Multi-output Gaussian Processes with Knowledge Transfer Across Domains. - Yusuke Tanaka 002; Toshiyuki Tanaka; Tomoharu Iwata; Takeshi Kurashima; Maya Okawa; Yasunori Akagi; Hiroyuki Toda (CoRR, 2022)

Context-aware spatio-temporal event prediction via convolutional Hawkes processes. - Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 002; Takeshi Kurashima; Hiroyuki Toda; Hisashi Kashima (Mach. Learn., 2022)

Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task. - Maya Okawa; Ekdeep Singh Lubana; Robert P. Dick; Hidenori Tanaka (NeurIPS, 2023)

Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model. - Mikail Khona; Maya Okawa; Jan Hula; Rahul Ramesh; Kento Nishi; Robert P. Dick; Ekdeep Singh Lubana; Hidenori Tanaka (ICML, 2024)

Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space. - Core Francisco Park; Maya Okawa; Andrew Lee 001; Ekdeep Singh Lubana; Hidenori Tanaka (NeurIPS, 2024)

Meta-Learning for Neural Network-based Temporal Point Processes. - Yoshiaki Takimoto; Yusuke Tanaka 002; Tomoharu Iwata; Maya Okawa; Hideaki Kim; Hiroyuki Toda; Takeshi Kurashima (CoRR, 2024)

Dynamics of Concept Learning and Compositional Generalization. - Yongyi Yang; Core Francisco Park; Ekdeep Singh Lubana; Maya Okawa; Wei Hu; Hidenori Tanaka (CoRR, 2024)

Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing. - Kento Nishi; Maya Okawa; Rahul Ramesh; Mikail Khona; Ekdeep Singh Lubana; Hidenori Tanaka (CoRR, 2024)

ICLR: In-Context Learning of Representations. - Core Francisco Park; Andrew Lee 001; Ekdeep Singh Lubana; Yongyi Yang; Maya Okawa; Kento Nishi; Martin Wattenberg; Hidenori Tanaka (ICLR, 2025)

Swing-by Dynamics in Concept Learning and Compositional Generalization. - Yongyi Yang; Core Francisco Park; Ekdeep Singh Lubana; Maya Okawa; Wei Hu; Hidenori Tanaka (ICLR, 2025)

Emergence of Hierarchical Emotion Organization in Large Language Models. - Bo Zhao 028; Maya Okawa; Eric J. Bigelow; Rose Yu; Tomer D. Ullman; Ekdeep Singh Lubana; Hidenori Tanaka (CoRR, 2025)