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A Nonparametric Framework for Quantifying Generative Inference on Neuromorphic Systems., , , and . CoRR, (2016)Kernel Distance Measures for Time Series, Random Fields and Other Structured Data., , and . Frontiers Appl. Math. Stat., (2021)A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA., , , and . CoRR, (2017)ApproxDBN: Approximate Computing for Discriminative Deep Belief Networks., , and . CoRR, (2017)PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems., , , , and . CoRR, (2019)Neuromorphic adaptations of restricted Boltzmann machines and deep belief networks., , , , and . IJCNN, page 1-6. IEEE, (2013)AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks., , and . CoRR, (2019)Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems., , , , and . CoRR, (2013)Gibbs Sampling with Low-Power Spiking Digital Neurons., , , , , , , , and . CoRR, (2015)Mapping Generative Models onto a Network of Digital Spiking Neurons., , , , , , , and . IEEE Trans. Biomed. Circuits and Systems, 10 (4): 837-854 (2016)