  Glitches represent a category of non-Gaussian and transient noise that
frequently intersects with gravitational wave (GW) signals, exerting a notable
impact on the processing of GW data. The inference of GW parameters, crucial
for GW astronomy research, is particularly susceptible to such interference. In
this study, we pioneer the utilization of temporal and time-spectral fusion
normalizing flow for likelihood-free inference of GW parameters, seamlessly
integrating the high temporal resolution of the time domain with the frequency
separation characteristics of both time and frequency domains. Remarkably, our
findings indicate that the accuracy of this inference method is comparable to
traditional non-glitch sampling techniques. Furthermore, our approach exhibits
greater efficiency, boasting processing times on the order of milliseconds. In
conclusion, the application of normalizing flow emerges as pivotal in handling
GW signals affected by transient noises, offering a promising avenue for
enhancing the field of GW astronomy research.
