A Forward-Propagation Rule for Acquiring Neural Inverse Models Using a RLS Algorithm. - Yoshihiro Ohama; Naohiro Fukumura; Yoji Uno (ICONIP, 2004)

A Simplified Forward-Propagation Learning Rule Applied to Adaptive Closed-Loop Control. - Yoshihiro Ohama; Naohiro Fukumura; Yoji Uno (ICANN (2), 2005)

A forward-propagation learning rule for neural inverse models using a method of recursive least squares. - Yoshihiro Ohama; Naohiro Fukumura; Yoji Uno (Syst. Comput. Jpn., 2005)

A forward-propagation learning rule for neural inverse models in consideration of the correlation of propagated errors. - Yoshihiro Ohama; Naohiro Fukumura; Yoji Uno (Syst. Comput. Jpn., 2006)

Toward a practical wall see-through system for drivers: How simple can it be? - Hiroshi Yasuda; Yoshihiro Ohama (ISMAR, 2012)

A Parallel Forward-Backward Propagation Learning Scheme for Auto-Encoders. - Yoshihiro Ohama; Takayoshi Yoshimura (ICONIP (2), 2017)

CIM: Constraint-based Intersection Management in Mixture of Non-Connected Vehicles. - Akinobu Fujii; Bunyo Okumura; Yoshihiro Ohama; Akihiro Nakamura; Kunihiro Goto; Tsukasa Shimizu (ITSC, 2021)

Improvements in Perpendicular Reverse Parking by Directing Drivers' Preliminary Behavior. - Yoshihiro Ohama; Kakeru Tanaka; Hiroshi Yasuda; Kainosuke Obata; Naohiro Fukumura (IEEE Access, 2021)

MARPF: Multi-Agent and Multi-Rack Path Finding. - Hiroya Makino; Yoshihiro Ohama; Seigo Ito (IROS, 2024)