A method of anomaly detection and energy-efficient inference determination includes receiving an input. A set of features of the input are extracted using an artificial neural network (ANN) to generate a latent representation of the input. A reconstruction of the input is generated using the ANN, based on the latent representation. A reconstruction error is computed based on the generated reconstruction and the input. The reconstruction error is compared to a predefined threshold to determine whether the in-distribution data or out-of-distribution data. An anomaly is detected in response to an out-of-distribution determination. A decision model is provided with the latent representation in response to the input being determined to be in-distribution data. In turn, the decision model computes an inference based on the latent representation.