9 papers
TwinPoSI: Statistical Twins for Powerful Post-Selection Inference on Population-Based Regression Coefficients
Changhu Wang, Zhifei Li, Jingyi Jessica Li
Post-selection inference (PoSI) quantifies uncertainty about regression coefficients after data-driven feature selection. A central question is the inferential target. Projection-b…
Spatial-Mode Selection for Local Mineral Absorption Spectroscopy
Qipeng Qian, Jialiang Jin, Shihao Wang +1
Absorption-band depth measures the fractional decrease in mineral reflectance below its local continuum. Recovering this feature strength for a small mineral region supports quanti…
QAM: Quadratic-Accurate Checkpoint Merging via Sequential Consistency
Shihao Wang, Rui Kong, Xinran Chen +7
Saved checkpoints record states along a training trajectory, but generally do not determine the updates at states that would be visited under a different schedule. We study how acc…
Shapley Valuation of Finite-Copy Quantum Data Depends on Physical Access
Qipeng Qian, Yuntao Qian
Data valuation asks how learning utility should be attributed to training data contributors. Most classical formulations begin after data have become reusable records, so the physi…
When Does Forecasting Reveal Temporal Structure? A Stability Analysis of Time-Series Structural Selection
Qipeng Qian, Yuntao Qian
Forecast accuracy is often used as a proxy for temporal structure discovery, but predictive performance and structural identifiability are not equivalent. Different temporal mechan…
Information-Calibrated Quantum Diffusion: Aligning Forward Noise with Reverse Recoverability
Qipeng Qian, Yuntao Qian
Quantum diffusion models typically parameterize forward corruption by raw channel strength, even though this parameter does not directly quantify how much ensemble information is e…
An Hybrid Quantum-Classical Diffusion Model for Image Generation
Qipeng Qian, Keli Deng, Yuntao Qian
Quantum diffusion models provide a physics-consistent route to generative learning by formulating noising and denoising directly on quantum states. However, applying such models to…
Learning Heat-based Equations in Self-similar variables
Shihao Wang, Qipeng Qian, Jingquan Wang
We study solution learning for heat-based equations in self-similar variables (SSV). We develop an SSV training framework compatible with standard neural-operator training. We inst…
Wavelet-Inspired Multiscale Graph Convolutional Recurrent Network for Traffic Forecasting
Qipeng Qian, Tanwi Mallick
Traffic forecasting is the foundation for intelligent transportation systems. Spatiotemporal graph neural networks have demonstrated state-of-the-art performance in traffic forecas…