The Hidden Power of Pure 16-bit Floating-Point Neural Networks. - Juyoung Yun; Byungkon Kang; Zhoulai Fu (CoRR, 2023)

In Defense of Pure 16-bit Floating-Point Neural Networks. - Juyoung Yun; Byungkon Kang; François Rameau; Zhoulai Fu (CoRR, 2023)

StochGradAdam: Accelerating Neural Networks Training with Stochastic Gradient Sampling. - Juyoung Yun (CoRR, 2023)

Mitigating Gradient Overlap in Deep Residual Networks with Gradient Normalization for Improved Non-Convex Optimization. - Juyoung Yun (IEEE Big Data, 2024)

Uncertainty Estimation for Tumor Prediction with Unlabeled Data. - Juyoung Yun; Shahira Abousamra; Chen Li 045; Rajarsi Gupta 001; Tahsin M. Kurç; Dimitris Samaras; Alison L. Van Dyke; Joel H. Saltz; Chao Chen 012 (CVPR Workshops, 2024)

Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks. - Juyoung Yun (IJCNN, 2024)

Analysis and Predictive Modeling of Solar Coronal Holes Using Computer Vision and LSTM Networks. - Juyoung Yun; Jungmin Shin (CoRR, 2024)

ZNorm: Z-Score Gradient Normalization for Accelerating Neural Network Training. - Juyoung Yun; Hoyoung Kim; Suin Cho; Hangil Kang (CoRR, 2024)

Sharpness-Aware Minimization with Z-Score Gradient Filtering for Neural Networks. - Juyoung Yun (CoRR, 2025)

Spectral and Temporal Denoising for Differentially Private Optimization. - Hyeju Shin; Kyudan Jung; Seongwon Yun; Juyoung Yun (CoRR, 2025)

Stochastic gradient sampling for enhancing neural networks training. - Juyoung Yun (Neural Comput. Appl., 2025)