#autoencoders articles

RSRahul Sai Indeevar Vrahul-ai.hashnode.devSep 5 · 9 min read

LLM Architectures: From BERT and GPT-2 to XLNet and T5

Understanding the internal mechanics of Large Language Model (LLM) architectures is crucial for building, fine-tuning, or deploying modern AI models. Why does GPT excel at text generation, while BERT

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SLShaun Liewshaunliew.hashnode.devJun 29, 2025 · 19 min read

Decoding Autoencoders: From Theory to Implementation

As I delved into the fascinating world of image generation and manipulation, I encountered autoencoders - a fundamental building block that bridges the gap between understanding and generating visual content. Let me share what I've learned about thes...

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KNKunal Nayyarkunal221.hashnode.devJun 5, 2025 · 17 min read

KL Divergence

Remember when we chatted about how AI models like Generative Adversarial Networks (GANs) learn to create? Well, there's another class of AI magicians : Variational Autoencoders (VAEs) and Diffusion Models, that achieve incredible feats of generation ...

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CKChandan Kumarliladhar.hashnode.devFeb 12, 2025 · 4 min read

Generative Adversarial Networks (GANs): An Overview

Generative Adversarial Networks (GANs) are a class of machine learning models designed for generative tasks, where they create new data samples similar to the given dataset. They consist of two neural networks, a Generator and a Discriminator, that c...

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CKChandan Kumarliladhar.hashnode.devFeb 12, 2025 · 3 min read

Denoising Autoencoders (DAEs): An In-Depth Overview

Introduction Denoising Autoencoders (DAEs) are a type of artificial neural network designed to remove noise from data while preserving meaningful features. Unlike traditional autoencoders, which aim to reconstruct input data, DAEs introduce noise to ...

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GDGabi Dobocanblog.telepat.ioNov 17, 2024 · 4 min read

Unveiling SCAR: Revolutionizing Large Language Models for Safe AI Deployment

Arxiv: https://arxiv.org/abs/2411.07122v1 PDF: https://arxiv.org/pdf/2411.07122v1.pdf Authors: Kristian Kersting, Patrick Schramowski, Björn Deiseroth, Manuel Brack, Felix Friedrich, Ruben Härle Published: 2024-11-11 In the vast ecosystem of artifi...

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GDGabi Dobocanblog.telepat.ioNov 17, 2024 · 3 min read

Understanding SCAR: Paving the Way for Safer AI Applications

Arxiv: https://arxiv.org/abs/2411.07122v1 PDF: https://arxiv.org/pdf/2411.07122v1.pdf Authors: Kristian Kersting, Patrick Schramowski, Björn Deiseroth, Manuel Brack, Felix Friedrich, Ruben Härle Published: 2024-11-11 Exploring the depths of AI tech...

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RBRiya Boseblogbyriyabose.hashnode.devSep 27, 2024 · 5 min read

Cracking the Code: Mastering Dimensionality Reduction Techniques in Machine Learning

Introduction In machine learning, we often work with datasets containing a large number of features or variables. While having more data might seem beneficial, high-dimensional datasets can lead to overfitting, increased computational costs, and redu...

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GSGayathri Selvaganapathiaienthusiast.hashnode.devAug 31, 2024 · 8 min read

Customer Segmentation Using Machine Learning

Table of Contents Introduction Understanding the Dataset Data Wrangling and Cleaning Exploratory Data Analysis (EDA) Unsupervised Learning Techniques K-Means Clustering Principal Component Analysis (PCA) Autoencoders 6. Visualizing Custom...

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MSMd Shahriyar Al Mustakim Mitulmitul-shahriyar.hashnode.devAug 8, 2024 · 9 min read

Machine Learning : Deep Learning - Stacked AutoEncoders (Part 31)

Autoencoders AutoEncoders are within Unsupervised Neural Networks. AutoEncoders look like this: Auto Encoder encodes itself. That it takes some sort of inputs, put some through a hidden layer, and then it gets outputs, but it aims for the outputs t...

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LLM Architectures: From BERT and GPT-2 to XLNet and T5

Decoding Autoencoders: From Theory to Implementation

KL Divergence

Generative Adversarial Networks (GANs): An Overview

Denoising Autoencoders (DAEs): An In-Depth Overview

Unveiling SCAR: Revolutionizing Large Language Models for Safe AI Deployment

Understanding SCAR: Paving the Way for Safer AI Applications

Cracking the Code: Mastering Dimensionality Reduction Techniques in Machine Learning

Customer Segmentation Using Machine Learning

Machine Learning : Deep Learning - Stacked AutoEncoders (Part 31)

#autoencoders

Search Hashnode

#autoencoders

Explore Hashnode

Trending tags this week

LLM Architectures: From BERT and GPT-2 to XLNet and T5

Decoding Autoencoders: From Theory to Implementation

KL Divergence

Generative Adversarial Networks (GANs): An Overview

Denoising Autoencoders (DAEs): An In-Depth Overview

Unveiling SCAR: Revolutionizing Large Language Models for Safe AI Deployment

Understanding SCAR: Paving the Way for Safer AI Applications

Cracking the Code: Mastering Dimensionality Reduction Techniques in Machine Learning

Customer Segmentation Using Machine Learning

Machine Learning : Deep Learning - Stacked AutoEncoders (Part 31)