Jinhao Sheng

Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling

Although artificial neural networks are often described as brain-inspired, their representations typically rely on continuous activations, such as the continuous latent variables in variational autoencoders (VAEs), which limits their biological plausibility compared to the discrete spike-based signa