Unsupervised learning and continual learning in neural networks

Unsupervised learning and continual learning in neural networks

<p>For decades research has pursued the ambitious goal of designing computer models that learn to solve problems as effectively as humans can. Artificial neural networks -- generic, optimizable models that were originally inspired by biological neurons in the brain -- appear to provide a promi...

Ամբողջական նկարագրություն

Մատենագիտական մանրամասներ
Հիմնական հեղինակ:	Ji, X
Այլ հեղինակներ:	Vedaldi, A
Ձևաչափ:	Թեզիս
Լեզու:	English
Հրապարակվել է:	2021
Խորագրեր:	Artificial intelligence Neural networks (Computer science) Computer vision

Նմանատիպ նյութեր

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Weed Density and Distribution Estimation for Precision Agriculture Using Semi-Supervised Learning
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Neural Network Preference Learning Approaches For Improving Agent-Based Meeting Scheduling Problems
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Review and analysis of deep neural network models for Alzheimer's disease classification using brain medical resonance imaging
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Celiac Disease Deep Learning Image Classification Using Convolutional Neural Networks
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Disrupted visual input unveils the computational details of artificial neural networks for face perception
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Federated learning for graph neural networks
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Adaptive memory networks with self-supervised learning for unsupervised anomaly detection
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Matching sensor ontologies with unsupervised neural network with competitive learning
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