Flow-Based Generative Modeling for Optimizing Sampling Policies in Compressed Sensing Applications 事件

Flow-Based Generative Modeling for Optimizing Sampling Policies in Compressed Sensing Applications arXiv:2606.00078v1 Announce Type: new Abstract: Numerous modern applications in signal processing and medical imaging necessitate acquiring high-dimensional signals under tight resource constraints. Traditional sampling theory suggests that accurate signal reconstruction requires a number of measurements proportional to the signal's ambient dimension, a requirement often too expensive or impractic