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www.daniellowengrub.com | ||
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jdlm.info
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| | | | | How many moves does it take to win a game of 2048? Find out using Markov chains! | |
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healeycodes.com
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| | | | | Generating random but familiar text by building Markov chains from scratch. | |
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www.ethanepperly.com
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| | | | | [AI summary] The user is discussing Markov Chain Monte Carlo (MCMC) methods, specifically the Metropolis-Hastings algorithm, applied to sampling from a distribution defined by a matrix $ A $. The focus is on the acceptance probability when transitioning between subsets $ S $ and $ S' $ of size $ k $, where the acceptance probability is determined by the ratio of determinants of submatrices of $ A $. The user is also exploring the computational complexity of these methods and their application to problems involving large matrices. | |
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neuralnetworksanddeeplearning.com
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| | | [AI summary] The text provides an in-depth explanation of the backpropagation algorithm in neural networks. It starts by discussing the concept of how small changes in weights propagate through the network to affect the final cost, leading to the derivation of the partial derivatives required for gradient descent. The explanation includes a heuristic argument based on tracking the perturbation of weights through the network, resulting in a chain of partial derivatives. The text also touches on the historical context of how backpropagation was discovered, emphasizing the process of simplifying complex proofs and the role of using weighted inputs (z-values) as intermediate variables to streamline the derivation. Finally, it concludes with a citation and licens... | ||
