3 papers
cs.LG2026
ODE-free Neural Flow Matching for One-Step Generative Modeling
Xiao Shou
Diffusion and flow matching models generate samples by learning time-dependent vector fields whose integration transports noise to data, requiring tens to hundreds of network evalu…
cs.LG2025
Gradient Flow Matching for Learning Update Dynamics in Neural Network Training
Xiao Shou, Yanna Ding, Jianxi Gao
Training deep neural networks remains computationally intensive due to the itera2 tive nature of gradient-based optimization. We propose Gradient Flow Matching (GFM), a continuous-…
cs.LG2025
Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation
Yanna Ding, Zijie Huang, Xiao Shou +3
Learning curve extrapolation predicts neural network performance from early training epochs and has been applied to accelerate AutoML, facilitating hyperparameter tuning and neural…