Leveraging Stochasticity And Randomness In Variational Autoencoders
Variational Autoencoders (VAEs) stand at the forefront of generative AI, harnessing the power of stochasticity to model complex data distributions and generate novel samples. By balancing deterministic algorithms with elements of randomness, VAEs achieve a delicate equilibrium that fosters robustness and versatility. This article delves into the intricacies of stochastic processes within VAEs, explores advanced…