Automating Inference, Learning, and Design using Probabilistic Programming

Hardware-Aware Probabilistic Machine Lea

📁 Hardware-Aware Probabilistic Machine Learning Models: Learning, Inference and Use Cases

✍ Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst 📂 Library 📅 2021 🏛 Springer 🌐 English

<p>This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device configuration may have on resource consumption and performance of the machine learning task, with the

Hardware-Aware Probabilistic Machine Lea

📁 Hardware-Aware Probabilistic Machine Learning Models: Learning, Inference and Use Cases

✍ Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst 📂 Library 📅 2021 🏛 Springer 🌐 English

<p>This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device configuration may have on resource consumption and performance of the machine learning task, with the

Hardware-Aware Probabilistic Machine Lea

📁 Hardware-Aware Probabilistic Machine Learning Models: Learning, Inference and Use Cases

✍ Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst 📂 Library 📅 2021 🏛 Springer 🌐 English

<p><span>This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device configuration may have on resource consumption and performance of the machine learning task, wit

Foundations of Probabilistic Logic Progr

📁 Foundations of Probabilistic Logic Programming. Languages, Semantics, Inference and Learning

✍ Fabrizio Riguzzi 📂 Library 📅 2018 🏛 River 🌐 English

Foundations of Probabilistic Logic Progr

📁 Foundations of Probabilistic Logic Programming: Languages, Semantics, Inference and Learning

✍ Fabrizio Riguzzi 📂 Library 📅 2023 🏛 River Publishers 🌐 English

The computational foundations of Artificial Intelligence (AI) are supported by two comer stones: logics and Machine Leaming. Computationallogic has found its realization in a number of frameworks for logic-based approaches to knowledge representation and automated reasoning, such as Logic Program m

Bayesian Methods for Hackers: Probabilis

📁 Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference

✍ Cameron Davidson-Pilon 📂 Library 📅 2015 🏛 Addison-Wesley Professional 🌐 English

Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial exam