ASAF
Adaptive Spline Activation Function
Stefano Guarnieri, Francesco Piazza, and Aurelio Uncini 
"Multilayer Feedforward Networks with Adaptive Spline Activation Function," 
 IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 10, NO. 3, MAY 1999

Abstract — In this paper, a new adaptive spline activation function neural network (ASNN) is presented. Due to the ASNN’s high representation capabilities, networks with a small number of interconnections can be trained to solve both pattern recognition and data processing real-time problems. The main idea is to use a Catmull–Rom cubic spline as the neuron’s activation function, which ensures a simple structure suitable for both software and hardware implementation. Experimental results demonstrate improvements in terms of generalization capability
and of learning speed in both pattern recognition and data processing tasks.
Index Terms— Adaptive activation functions, function shape autotuning, generalization, generalized sigmoidal functions, multilayer
perceptron, neural networks, spline neural networks.
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization
https://paperswithcode.com/paper/adversarial-soft-advantage-fitting-imitation
Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization