1 citations · 1 across the 1 of their papers we have counts for
4 papers
Revisiting 16-bit Neural Network Training: A Practical Approach for Resource-Limited Learning
Juyoung Yun, Sol Choi, Francois Rameau +2
With the increasing complexity of machine learning models, managing computational resources like memory and processing power has become a critical concern. Mixed precision techniqu…
Stabilizing Backpropagation in 16-bit Neural Training with Modified Adam Optimizer
Juyoung Yun
In this research, we address critical concerns related to the numerical instability observed in 16-bit computations of machine learning models. Such instability, particularly when…
Predictive Modeling of Coronal Hole Areas Using Long Short-Term Memory Networks
Juyoung Yun
In the era of space exploration, the implications of space weather have become increasingly evident. Central to this is the phenomenon of coronal holes, which can significantly inf…
The Hidden Power of Pure 16-bit Floating-Point Neural Networks
Juyoung Yun, Byungkon Kang, Zhoulai Fu
Lowering the precision of neural networks from the prevalent 32-bit precision has long been considered harmful to performance, despite the gain in space and time. Many works propos…