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Found 5 papers, 3 papers with code
Switch EMA: A Free Lunch for Better Flatness and Sharpness
Exponential Moving Average (EMA) is a widely used weight averaging (WA) regularization to learn flat optima for better generalizations without extra cost in deep neural network (DNN) optimization.
SemiReward: A General Reward Model for Semi-supervised Learning
The main challenge is how to distinguish high-quality pseudo labels against the confirmation bias.
Multi-scale Fusion Fault Diagnosis Method Based on Two-Dimensionaliztion Sequence in Complex Scenarios
Rolling bearings are critical components in rotating machinery, and their faults can cause severe damage.
Interpretable ODE-style Generative Diffusion Model via Force Field Construction
This paper aims to identify various physical models that are suitable for constructing ODE-style generative diffusion models accurately from a mathematical perspective.
OpenMixup: A Comprehensive Mixup Benchmark for Visual Classification
Data mixing, or mixup, is a data-dependent augmentation technique that has greatly enhanced the generalizability of modern deep neural networks.
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