Novelty signals in the brain modulate learning and drive exploratory behaviors in humans and animals. While the perceived novelty of a stimulus is known to depend on previous experience, the effect of stimulus representations on novelty computation remains elusive. In particular, existing models of novelty computation fail to account for the effects of stimulus similarities that are abundant in naturalistic environments and tasks. Here, we present a unifying, biologically plausible model that captures how stimulus representations modulate novelty signals in the brain and influence novelty-driven learning and exploration. By applying our model to two publicly available data sets, we quantify and explain (i) how generalization across similar visual stimuli affects novelty responses in the mouse visual cortex, and (ii) how generalization across nearby locations impacts mouse exploration in an unfamiliar environment. Our model unifies and explains distinct neural and behavioral signatures of novelty, and enables theory-driven experiment design to investigate the neural mechanisms of novelty computation.