3 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
Once-for-All: Scalable Simultaneous Forecasting via Equilibrium State Estimation
Beinan Xu, Andy Song, Jiti Gao +1
We introduce Equilibrium State Estimation (ESE), a novel paradigm for simultaneous prediction, where multiple interacting systems require separate yet coordinated forecasts. Such s…
Zero-Shot Neural Network Evaluation with Sample-Wise Activation Patterns
Yameng Peng, Andy Song, HaythamM. Fayek +2
Zero-shot proxies, also known as training-free metrics, are widely adopted to reduce the computational overhead in neural network evaluation for scenarios such as Neural Architectu…
Distributional Statistics Restore Training Data Auditability in One-step Distilled Diffusion Models
Muxing Li, Zesheng Ye, Sharon Li +3
The proliferation of diffusion models trained on web-scale, provenance-uncertain image collections has made it essential, yet technically unresolved, to determine whether a model h…
SWAP-NAS: Sample-Wise Activation Patterns for Ultra-fast NAS
Yameng Peng, Andy Song, Haytham M. Fayek +2
Training-free metrics (a.k.a. zero-cost proxies) are widely used to avoid resource-intensive neural network training, especially in Neural Architecture Search (NAS). Recent studies…