The present disclosure provides systems and methods that leverage machine learning to predict multiple touch interpretations. In particular, the systems and methods of the present disclosure can include and use a machine-learned touch interpretation prediction model that has been trained to receive touch sensor data indicative of one or more locations of one or more user input objects relative to a touch sensor at one or more times and, in response to receipt of the touch sensor data, provide one or more predicted touch interpretation outputs. Each predicted touch interpretation output corresponds to a different type of predicted touch interpretation based at least in part on the touch sensor data. Predicted touch interpretations can include a set of touch point interpretations, a gesture interpretation, and/or a touch prediction vector for one or more future times.