New Method for Dispatching Waiting Logical Processors in Virtual Machine Systems. - Hidenori Umeno; Masato Kiyama; Takafumi Fukunaga; Takashige Kubo (COMPSAC (1), 2005)

Parallel Computations Reveal Hidden Errors of Commonly Used Random Number Generators. - Hyo Ashihara; Ai Kuramoto; Isaku Wada; Makoto Matsumoto; Hironori Kikuchi; Masato Kiyama (CSC, 2006)

A Quantized Neural Network Library for Proper Implementation of Hardware Emulation. - Masato Kiyama; Yasuhiro Nakahara; Motoki Amagasaki; Masahiro Iida (CANDAR Workshops, 2019)

Deep Learning Framework with Arbitrary Numerical Precision. - Masato Kiyama; Motoki Amagasaki; Masahiro Iida (MCSoC, 2019)

A Novel SLM-Based Virtual FPGA Overlay Architecture. - Theingi Myint; Motoki Amagasaki; Qian Zhao 001; Masahiro Iida; Masato Kiyama (MCSoC, 2019)

Relationship between Recognition Accuracy and Numerical Precision in Convolutional Neural Network Models. - Yasuhiro Nakahara; Masato Kiyama; Motoki Amagasaki; Masahiro Iida (IEICE Trans. Inf. Syst., 2020)

Multi-Time-Scale Input Approaches for Hourly-Scale Rainfall-Runoff Modeling based on Recurrent Neural Networks. - Kei Ishida; Masato Kiyama; Ali Ercan; Motoki Amagasaki; Tongbi Tu; Makoto Ueda (CoRR, 2021)

Capabilities of Deep Learning Models on Learning Physical Relationships: Case of Rainfall-Runoff Modeling with LSTM. - Kazuki Yokoo; Kei Ishida; Ali Ercan; Tongbi Tu; Takeyoshi Nagasato; Masato Kiyama; Motoki Amagasaki (CoRR, 2021)

Development of Quantized DNN Library for Exact Hardware Emulation. - Masato Kiyama; Motoki Amagasaki; Masahiro Iida (CoRR, 2021)

Use of 1D-CNN for input data size reduction of LSTM in Hourly Rainfall-Runoff modeling. - Kei Ishida; Ali Ercan; Takeyoshi Nagasato; Masato Kiyama; Motoki Amagasaki (CoRR, 2021)

Extension of Convolutional Neural Network along Temporal and Vertical Directions for Precipitation Downscaling. - Takeyoshi Nagasato; Kei Ishida; Ali Ercan; Tongbi Tu; Masato Kiyama; Motoki Amagasaki; Kazuki Yokoo (CoRR, 2021)

Reconfigurable Neural Network Accelerator and Simulator for Model Implementation. - Yasuhiro Nakahara; Masato Kiyama; Motoki Amagasaki; Qian Zhao 001; Masahiro Iida (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2022)

A Posit Based Multiply-accumulate Unit with Small Quire Size for Deep Neural Networks. - Yasuhiro Nakahara; Yuta Masuda; Masato Kiyama; Motoki Amagasaki; Masahiro Iida (IPSJ Trans. Syst. LSI Des. Methodol., 2022)

A Deep Neural Network Translator for Edge Site Implementation. - Mery Diana; Masato Kiyama; Motoki Amagasaki; Masayoshi Ito; Yuki Morishita (CANDARW, 2023)

A Lightweight Deep Neural Network Using a Mixer-Type Nonlinear Vector Autoregression. - Mery Diana; Ridhwan Amin; Motoki Amagasaki; Masato Kiyama (IEEE Access, 2023)

Multi-Camera People Tracking With Spatio-Temporal and Group Considerations. - Shoki Sakaguchi; Motoki Amagasaki; Masato Kiyama; Toshiaki Okamoto (IEEE Access, 2024)

A simple DNN regression for the chemical composition in essential oil. - Yuki Harada; Shuichi Maeda; Masato Kiyama; Shinichiro Nakamura (CoRR, 2024)

Advanced Implementation of DNN Translator using ResNet9 for Edge Devices. - Mery Diana; Masato Kiyama; Motoki Amagasaki; Masayoshi Ito; Yuki Morishita (Int. J. Netw. Comput., 2024)

Evaluation of Trade-Off Between Compression Ratio and Hardware Cost for Adaptive Bandwidth Compression Hardware Platform. - Tomohiro Ueno; Kaito Kitazume; Masato Kiyama; Kazutomo Yoshii; Kento Sato; Norihisa Fujita; Ryohei Kobayashi 001; Taisuke Boku; Kentaro Sano (COOL CHIPS, 2025)

Enhancing FPGA Routing Efficiency with Graph Neural Network-Based Congestion Prediction. - Kazuki Tokuishi; Motoki Amagasaki; Masato Kiyama; Kenshu Seto (HEART, 2025)

ENDNet: Extra-Node Decision Network for Subgraph Matching. - Masaki Shirotani; Motoki Amagasaki; Masato Kiyama (IEEE Access, 2025)