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This paper proposes an online method for warped Gaussian processes that jointly updates latent GP moments and optimizes warping parameters using exact recursive gradient computation.
Stanford CS224N course notes provide a clear introduction to the mathematics of backpropagation and gradient computation in neural networks, covering chain rule, computational graphs, and vectorized derivatives.