[ad_1] Introduction Modular neural networks have been gaining attention in recent years due to their ability to enhance compositionality in neural networks. Compositionality refers to the capacity of a system to combine simpler components to…
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[ad_1] Introduction Federated learning is a decentralized machine learning approach that allows multiple parties to collaboratively train a global model without sharing their data. This approach addresses privacy concerns and data security issues associated with…
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[ad_1] Introduction Bayesian neural networks (BNNs) have gained significant attention in recent years due to their ability to provide uncertainty estimates in neural network models. This is crucial in various applications such as medical diagnosis,…
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[ad_1] Introduction: Self-attention networks have gained significant attention in the field of artificial intelligence and machine learning due to their ability to capture global dependencies in data. These networks have shown promising results in various…
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[ad_1] Introduction Chapter 1: Introduction 1.1 The Introduction 1.2 Background of Study 1.3 Problem Statement 1.4 Objective of Study 1.5 Limitation of Study 1.6 Scope of Study 1.7 Significance of Study 1.8 Structure of the…
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[ad_1] Introduction: In recent years, deep learning has revolutionized the field of computer vision by achieving unprecedented levels of accuracy in various tasks, such as image classification, object detection, and segmentation. One key component of…
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[ad_1] Introduction Convolutional neural networks (CNNs) have gained significant importance in recent years for their ability to effectively extract and learn features from grid-like data such as images, videos, and sensor data. This thesis focuses…
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[ad_1] Introduction Attention mechanisms have become a crucial component in various fields such as natural language processing, computer vision, and machine learning. These mechanisms allow models to focus on important parts of the input data…
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[ad_1] Introduction Normalizing flows have emerged as a powerful tool for flexible density estimation in recent years. These methods allow for the modeling of complex, multi-modal distributions by transforming a simple base distribution into the…
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[ad_1] Introduction: In recent years, there has been a growing interest in developing robust machine learning models that can perform well in the presence of adversarial attacks. These attacks are designed to exploit vulnerabilities in…
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