Mixed Precision Weight Networks: Training Neural Networks with Varied Precision Weights. - Ninnart Fuengfusin; Hakaru Tamukoh (ICONIP (2), 2018)

Network with Sub-Networks. - Ninnart Fuengfusin; Hakaru Tamukoh (CoRR, 2019)

Network with Sub-networks: Layer-wise Detachable Neural Network. - Ninnart Fuengfusin; Hakaru Tamukoh (J. Robotics Netw. Artif. Life, 2021)

A Sub-Model Detachable Convolutional Neural Network. - Ninnart Fuengfusin; Hakaru Tamukoh (J. Robotics Netw. Artif. Life, 2021)

INT8 Activation Ternary or Binary Weights Networks: Unifying Between INT8 and Lower-bit Width Quantization. - Ninnart Fuengfusin; Hakaru Tamukoh (J. Robotics Netw. Artif. Life, 2022)

Efficient Repetition Coding for Deep Learning Towards Implementation Using Emerging Non-Volatile Memory with Write-Errors. - Ninnart Fuengfusin; Hakaru Tamukoh; Yuichiro Tanaka; Osamu Nomura; Takashi Morie (IJCNN, 2023)

Robust Binary Encoding for Ternary Neural Networks Toward Deployment on Emerging Memory. - Ninnart Fuengfusin; Hakaru Tamukoh; Osamu Nomura; Takashi Morie (IJCNN, 2024)

Harden Deep Neural Networks Against Fault Injections Through Weight Scaling. - Ninnart Fuengfusin; Hakaru Tamukoh (CoRR, 2024)

Enhancing Neural Network Robustness Against Fault Injection Through Non-linear Weight Transformations. - Ninnart Fuengfusin; Hakaru Tamukoh (CoRR, 2024)

Towards Optimizing Physical Reservoir Computing: A Hybrid PCPO-ESN Framework for Time Series Forecasting. - Dinda Pramanta; Ninnart Fuengfusin; Arie Rachmad Syulistyo; Hakaru Tamukoh (ISCAS, 2025)