activity
20122024
most citedPredicting Opinion Dynamics via Sociologically-Informed Neural Networks

30 citations · 67 across the 13 of their papers we have counts for

collaborators

7 papers

eess.SY20221 cited

Data-driven End-to-end Learning of Pole Placement Control for Nonlinear Dynamics via Koopman Invariant Subspaces

Tomoharu Iwata, Yoshinobu Kawahara

We propose a data-driven method for controlling the frequency and convergence rate of black-box nonlinear dynamical systems based on the Koopman operator theory. With the proposed…

cs.SI202230 cited

Predicting Opinion Dynamics via Sociologically-Informed Neural Networks

Maya Okawa, Tomoharu Iwata

Opinion formation and propagation are crucial phenomena in social networks and have been extensively studied across several disciplines. Traditionally, theoretical models of opinio…

stat.ML2021

Training Deep Models to be Explained with Fewer Examples

Tomoharu Iwata, Yuya Yoshikawa

Although deep models achieve high predictive performance, it is difficult for humans to understand the predictions they made. Explainability is important for real-world application…

stat.ML20141 cited

Multi-view Anomaly Detection via Probabilistic Latent Variable Models

Tomoharu Iwata, Makoto Yamada

We propose a nonparametric Bayesian probabilistic latent variable model for multi-view anomaly detection, which is the task of finding instances that have inconsistent views. With…

cs.SI20147 cited

Collaboration on Social Media: Analyzing Successful Projects on Social Coding

Yuya Yoshikawa, Tomoharu Iwata, Hiroshi Sawada

Social Coding Sites (SCSs) are social media services for sharing software development projects on the Web, and many open source projects are currently being developed on SCSs. One…

cs.LG201414 cited

Warped Mixtures for Nonparametric Cluster Shapes

Tomoharu Iwata, David Duvenaud, Zoubin Ghahramani

A mixture of Gaussians fit to a single curved or heavy-tailed cluster will report that the data contains many clusters. To produce more appropriate clusterings, we introduce a mode…