Bokus

Vadim Sokolov – författare

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4 produkter

  1. Nick Polson, Vadim Sokolov - Bayes, AI, and Deep Learning, Inbunden. Tillgänglighet: Kommande

    Bayes, AI, and Deep Learning

    Foundations of Data Science

    Av Nick Polson, Vadim Sokolov

    Inbunden, 2027

    2713 kr

    Kommande

    From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian …

  2. Nick Polson, Vadim Sokolov - Bayes, AI, and Deep Learning, Häftad. Tillgänglighet: Kommande

    Bayes, AI, and Deep Learning

    Foundations of Data Science

    Av Nick Polson, Vadim Sokolov

    Häftad, 2027

    1015 kr

    Kommande

    From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian …

  3. Nicholas G. Polson, Vadim Sokolov - Generative Bayesian Computation, Häftad. Tillgänglighet: Kommande

    Generative Bayesian Computation

    Quantile Neural Networks for Inference and Surrogates

    Av Nicholas G. Polson, Vadim Sokolov

    Häftad, 2027

    971 kr

    Kommande

    This book introduces Generative Bayesian Computation (GBC), a transformative framework that replaces traditional Markov chain Monte Carlo methods with deep quantile neural networks trained by stochastic gradient descent. At its core, GBC leverages the noise outsourcing theorem and implicit quantile …

  4. Nicholas G. Polson, Vadim Sokolov - Generative Bayesian Computation, Inbunden. Tillgänglighet: Kommande

    Generative Bayesian Computation

    Quantile Neural Networks for Inference and Surrogates

    Av Nicholas G. Polson, Vadim Sokolov

    Inbunden, 2027

    2713 kr

    Kommande

    This book introduces Generative Bayesian Computation (GBC), a transformative framework that replaces traditional Markov chain Monte Carlo methods with deep quantile neural networks trained by stochastic gradient descent. At its core, GBC leverages the noise outsourcing theorem and implicit quantile …