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Matthias Karlbauer
Artificial Neural Networks for Knowledge Extraction in Spatiotemporal Dynamics and Weather Forecasting

This thesis explores the potential of machine learning methods for improving weather forecasts. Since weather is considered a spatiotemporal process that evolves over space through time, the thesis first …

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Keita Broadwater, Namid Stillman
Graph Neural Networks in Action

About the bookIn Graph Neural Networks in Action you will create deep learning models that are perfect for working with interconnected graph data. Start with a comprehensive introduction to graph data's u…

lieferbar ab 2.7.2025.

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Muhammad Arsalan
Optimization of Spiking Neural Networks for Radar Applications

This book offers a comprehensive exploration of the transformative role that edge devices play in advancing Internet of Things (IoT) applications. By providing real-time processing, reduced latency, incre…

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Kishore Bingi, Venkata Ramana Kasi, Ramadevi Bhukya
Fractional-Order Activation Functions for Neural Networks

This book suggests the development of single and multi-layer fractional-order neural networks that incorporate fractional-order activation functions derived using fractional-order derivatives. Activation …

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Ghada Alsuhli, Vasilis Sakellariou, Thanos Stouraitis, Mahmoud Al-Qutayri
Number Systems for Deep Neural Network Architectures

This book provides readers a comprehensive introduction to alternative number systems for more efficient representations of Deep Neural Network (DNN) data. Various number systems (conventional/unconventio…

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Svetlin Georgiev
Neural Network Methods for Dynamic Equations on Time Scales

This book aims to handle dynamic equations on time scales using artificial neural network (ANN). Basic facts and methods for ANN modeling are considered. The multilayer artificial neural network (ANN) mod…

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Claudio Conti
Quantum Machine Learning

This book presents a new way of thinking about quantum mechanics and machine learning by merging the two. Quantum mechanics and machine learning may seem theoretically disparate, but their link becomes cl…

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Trefferliste "Graph Neural Networks For Explainability" - alle Bücher

Matthias Karlbauer Artificial Neural Networks for Knowledge Extraction in Spatiotemporal Dynamics and Weather Forecasting

Keita Broadwater, Namid Stillman Graph Neural Networks in Action

Muhammad Arsalan Optimization of Spiking Neural Networks for Radar Applications

Kishore Bingi, Venkata Ramana Kasi, Ramadevi Bhukya Fractional-Order Activation Functions for Neural Networks

Ghada Alsuhli, Vasilis Sakellariou, Thanos Stouraitis, Mahmoud Al-Qutayri Number Systems for Deep Neural Network Architectures

Svetlin Georgiev Neural Network Methods for Dynamic Equations on Time Scales

Claudio Conti Quantum Machine Learning

Matthias Karlbauer
Artificial Neural Networks for Knowledge Extraction in Spatiotemporal Dynamics and Weather Forecasting

Keita Broadwater, Namid Stillman
Graph Neural Networks in Action

Muhammad Arsalan
Optimization of Spiking Neural Networks for Radar Applications

Kishore Bingi, Venkata Ramana Kasi, Ramadevi Bhukya
Fractional-Order Activation Functions for Neural Networks

Ghada Alsuhli, Vasilis Sakellariou, Thanos Stouraitis, Mahmoud Al-Qutayri
Number Systems for Deep Neural Network Architectures

Svetlin Georgiev
Neural Network Methods for Dynamic Equations on Time Scales

Claudio Conti
Quantum Machine Learning