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Neural Information Processing

follows: adversarial networks and learning; convolutional neural networks; deep neural networks; embeddings and feature fusion; human centred;

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Brits Speak Out

This work introduces concepts and algorithms in optimization theory for neural network research, covers the main neural network models and;

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Introduction to the Theory of Neural Computation

Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides;

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Introduction to the Theory of Neural Computation

Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides;

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Neural Networks and Psychopathology

Research on connectionist models is one of the most exciting areas in cognitive science, and neural network models of psychopathology have;

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Neural Networks and Psychopathology

Research on connectionist models is one of the most exciting areas in cognitive science, and neural network models of psychopathology have;

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Neural Network Models

Providing an in-depth treatment of neural network models, this volume explains and proves the main results in a clear and accessible way;

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PyTorch Recipes

Learn how to use PyTorch to build neural network models using code snippets updated for this second edition. This book includes new;

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Neural Networks with R

Uncover the power of artificial neural networks by implementing them through R code. About This Book * Develop a strong background;

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Epigenesis in neural network models of cognitive development

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Neural Network Methods in Natural Language Processing

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data;

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Neural Network Methods in Natural Language Processing

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data;

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Semi-empirical Neural Network Modeling and Digital Twins Development

Semi-empirical Neural Network Modeling presents a new approach on how to quickly construct an accurate, multilayered neural network;

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Mastering PyTorch

PyTorch 1.x to build advanced neural network models Learn to perform a wide range of tasks by implementing deep learning algorithms and;

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Building Neural Networks

This practical introduction describes the kinds of real-world problems neural network technology can solve. Surveying a range of neural;

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Network Models for Control and Processing

related fields. These cover: control processes, modelling features and operations of biological neural networks and neurons, simulation;

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Neural Networks Modeling and Control

Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and;

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Practical Neural Network Recipes In C++

This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming;

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Neural Network Programming with Python

This book is a guide on how to implement a neural network in the Python programming language. It begins by giving you a brief overview;

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Caffe2 Quick Start Guide

Build and train scalable neural network models on various platforms by leveraging the power of Caffe2 Key Features Migrate models trained;

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Neural Information Processing

; learning from incomplete data; model compression and optimisation; neural learning models; neural network applications; and social network;

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Neural Networks in Transport Applications

of neural network analysis for research applications in the transportation sector. It does not only focus on engineering types of approaches, but;

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The Mind Within the Net

/>Neurophysiology has told us a lot about how neurons work; neural network theory is about how neurons work together to process;

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Automated Deep Learning Using Neural Network Intelligence

Optimize, develop, and design PyTorch and TensorFlow models for a specific problem using the Microsoft Neural Network Intelligence (NNI;

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Connectionist Models in Cognitive Psychology

Connectionist Models in Cognitive Psychology is a state-of-the-art review of neural network modelling in core areas of cognitive psychology;

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Connectionist Models in Cognitive Psychology

Connectionist Models in Cognitive Psychology is a state-of-the-art review of neural network modelling in core areas of cognitive psychology;

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Neural Network Models of Conditioning and Action

challenging phenomena - and neural network models provide a natural framework for representing and analysing such interactions - all the articles;

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