Systems, techniques, and computer-program products that, individually and in combination, permit machine condition monitoring are provided. In some aspects, state estimation and anomaly localization can be determined jointly. To that end, in some embodiments, systems can be configured using at least a synthetic training dataset. The synthetic training dataset includes sensor output data that incorporates synthetic a random amount of noise to each one of multiple sensor devices that probe an industrial machine. The training dataset also includes synthetic information indicative of location of anomalous sensor device(s) of the multiple sensor devices. Therefore, the systems can learn to determine state estimation and anomalous localization concurrently, in a single operation. Accordingly, the training of the systems is consistent with the operation of the systems during machine condition monitoring. Embodiments of the disclosure provide superior predictive performance over conventional machine condition monitoring approaches.