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This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.
The aim of this work is to generate new face images similar to training ones (the CelebA dataset) according to user specified attributes. To do that we ended up with an implementation of a Versatile Auxiliary Classifier + GAN.
MSc Thesis on Conditional dMRI Generative AI Models and their applicability in the decreasing scan acquisition times and bettering of patient's quality of life.