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Implementation of the NICE (Non-linear Independent Components Estimation) flow model for generative modeling, applied to MNIST and Fashion-MNIST datasets.

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NICE: Non-linear Independent Components Estimation

NICE (Non-linear Independent Components Estimation) is a flow-based generative model for density estimation and sample generation, leveraging reversible transformations for efficient computation.

This repository implements both Additive and Affine coupling layers, tested on MNIST and Fashion-MNIST datasets. Results include loss plots and generated samples.

For more details, refer to the original paper NICE: Non-linear Independent Components Estimation By Laurent Dinh, David Krueger, and Yoshua Bengio (2015) Link

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Implementation of the NICE (Non-linear Independent Components Estimation) flow model for generative modeling, applied to MNIST and Fashion-MNIST datasets.

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