A computer system (102, 130) comprising: one or more processors (112, 132); and one or more non-transitory computer readable media (114, 134) that collectively store: a machine-learned spiking neural network (120, 140) that comprises one or more spiking neurons that have an activation layer that uses a double exponential function to model a leaky input that an incoming neuron spike provides to a membrane potential of the spiking neuron; and instructions (118, 138) that, when executed by the one or more processors, cause the computer system to perform operations, the operations comprising: obtaining a network input; implementing the machine-learned spiking neural network (120, 140) to process the network input; and receiving a network output generated by the machine-learned spiking neural network (120, 140) as a result of processing the network input; wherein the network input comprises audio data and the network output is a speech recognition output; or wherein the network input comprises audio or video data and the network output comprises a classification of the network input. one or more processors (112, 132); and one or more non-transitory computer readable media (114, 134) that collectively store: a machine-learned spiking neural network (120, 140) that comprises one or more spiking neurons that have an activation layer that uses a double exponential function to model a leaky input that an incoming neuron spike provides to a membrane potential of the spiking neuron; and instructions (118, 138) that, when executed by the one or more processors, cause the computer system to perform operations, the operations comprising: obtaining a network input; implementing the machine-learned spiking neural network (120, 140) to process the network input; and receiving a network output generated by the machine-learned spiking neural network (120, 140) as a result of processing the network input; wherein the network input comprises audio data and the network output is a speech recognition output; or wherein the network input comprises audio or video data and the network output comprises a classification of the network input. a machine-learned spiking neural network (120, 140) that comprises one or more spiking neurons that have an activation layer that uses a double exponential function to model a leaky input that an incoming neuron spike provides to a membrane potential of the spiking neuron; and instructions (118, 138) that, when executed by the one or more processors, cause the computer system to perform operations, the operations comprising: obtaining a network input; implementing the machine-learned spiking neural network (120, 140) to process the network input; and receiving a network output generated by the machine-learned spiking neural network (120, 140) as a result of processing the network input; wherein the network input comprises audio data and the network output is a speech recognition output; or wherein the network input comprises audio or video data and the network output comprises a classification of the network input. obtaining a network input; implementing the machine-learned spiking neural network (120, 140) to process the network input; and receiving a network output generated by the machine-learned spiking neural network (120, 140) as a result of processing the network input; wherein the network input comprises audio data and the network output is a speech recognition output; or wherein the network input comprises audio or video data and the network output comprises a classification of the network input.