Sources

• Guide to convolution: https://arxiv.org/pdf/1603.07285.pdf
• Convolutional backpropegation: https://medium.com/@pavisj/convolutions-and-backpropagations-46026a8f5d2c
• Extra info on partial convolution: https://arxiv.org/pdf/1804.07723.pdf
• Partial convolution based padding: https://arxiv.org/pdf/1811.11718.pdf
• Wasserstein GAN: https://arxiv.org/pdf/1701.07875.pdf
• Wasserstein GAN tutorial: https://machinelearningmastery.com/how-to-code-a-wasserstein-generative-adversarial-network-wgan-from-scratch/
• Wasserstein loss tutorial: https://machinelearningmastery.com/how-to-implement-wasserstein-loss-for-generative-adversarial-networks/