Reviews: SplineNets: Continuous Neural Decision Graphs

The paper presents SplineNets that reformulate CNNs as neural decision graph using B-splines. It's comprised of four technical contributions, i.e., embedding trick, general formulation for a neural decision graph, a loss function of utilizing and specializing splines and a differentiable quantization method. The idea is novel and sensible. It integrates the classic splines into convolutional neural networks which might be valuable for both of theoretical and practical aspects. However, the paper is difficult to read and follow.